Test AI Research Against Similar Company Names
Use a synthetic entity-collision pack to catch mixed-company facts and preserve unresolved identity before account enrichment.
10/24/20263 min read
An AI research assistant can combine accurate facts into a false account when several organizations share a name. The individual sentences may all be sourced, yet the resulting brief describes a company that does not exist. Evaluate entity separation before assessing whether the prose is useful.
This is not a name-cleaning exercise. The task is to test whether facts stay attached to the correct organization and whether unresolved identity remains unresolved. Normalizing spaces or legal suffixes does not establish that two records represent the same entity.
Construct a collision pack
Use synthetic organizations so the test does not expose real customer data or imply a relationship between actual companies. Give each entity enough distinguishing context to support an answer, plus one deliberately ambiguous passage. Keep the identity key separate from the preferred display name.
The fictional pack contains E1, “Harbor Metric Ltd,” a laboratory equipment distributor in Bristol; E2, “Harbor Metrics GmbH,” an industrial analytics developer in Hamburg; and E3, “Harbor Metric Services,” a repair division explicitly described as part of E1. The packet provides unique internal fixture IDs, not purported registry identifiers.
Source P1 says E1 opened a repair workshop. P2 says E2 released a software update. P3 states E3 handles repairs for E1. P4 says only “Harbor Metric is hiring engineers,” with no location, identifier or relationship evidence. P4 is intentionally insufficient for attribution.
Define the required output
Ask for an account note for E1 only, with a separate unresolved-identity section. The expected note includes the repair workshop and the documented E3 relationship. It excludes E2's software update. The hiring statement stays unattributed unless further evidence identifies its subject.
Use this filled mapping artifact:
P1 → E1; workshop event; identity supported by exact fixture reference; eligible for E1 note.
P2 → E2; software event; similar name but different identity; excluded from E1 note.
P3 → E3 related to E1; repair responsibility; relationship explicit; include with division scope.
P4 → unresolved candidate; hiring event; no reliable identity discriminator; hold outside account facts.
An illustrative failure says, “Harbor Metric opened a repair workshop and launched industrial analytics software.” Both clauses came from the packet, but their combination contaminates E1 with E2 evidence. Mark it an entity-assignment failure rather than a general hallucination. The repair is to separate records, not to rewrite the sentence more cautiously.
Probe shortcuts without making the task impossible
Rename E2 to a less similar name while preserving its facts. If contamination disappears, the near-name collision is likely relevant to the failure. Then restore the similar name and move P2 next to P1. The correct assignment should not change because neighboring passages look related.
Remove the explicit E3 relationship from a variant. The model should no longer present E3 as a division of E1. It may identify a possible relationship for review, but the shared name alone cannot establish one. Finally, add a verified fixture statement identifying P4's subject as E2. The formerly unresolved hiring fact should now attach to E2, not remain globally unknown.
Do not demand disambiguation when the test supplies no disambiguating evidence. A case can legitimately end in “identity not established.” Reviewers should distinguish failure to use available evidence from appropriate caution when evidence is absent.
Record contamination at the claim level
Score each source-to-entity mapping and the final account summary. A correct mapping table followed by a mixed summary still fails the complete workflow. Track the number of wrong assignments, unresolved facts wrongly promoted and supported facts omitted. Keep relationship errors separate from identity errors because a division and its parent are related without being interchangeable.
NIST recommends checking generated evidence and citations. In this test, that check includes the source's subject. Stop account enrichment when identity remains uncertain, and route the specific ambiguous passage to a researcher. Passing a small collision pack supports only the tested conditions; it does not authorize automatic merges, unrestricted research or confidence in every similarly named company.
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