Triple
T13425196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthropic |
E313461
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object | Tom Henighan |
E461713
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Tom Henighan | Statement: [Anthropic, foundedBy, Tom Henighan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Henighan Context triple: [Anthropic, foundedBy, Tom Henighan]
-
A.
Tom Henighan
chosen
Tom Henighan is a researcher and co-author known for his work in large-scale language models and AI, including contributions to influential OpenAI publications.
-
B.
Jack McHale
Jack McHale is a relatively obscure individual known primarily as a namesake referenced in records of notable bearers of the surname McHale.
-
C.
Tom Hickey
Tom Hickey was an Irish actor known for his extensive work in theatre, film, and television, particularly in Ireland.
-
D.
Eddie Cahill
Eddie Cahill is an American actor best known for his role as Detective Don Flack on the television series CSI: NY.
-
E.
Nick O'Hagan
Nick O'Hagan is a film producer best known for his work on the British World War II-era thriller "Glorious 39."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed066408190a416880affd8416e |
completed | April 12, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd46686c288190a51847f86785568a |
completed | May 8, 2026, 2:11 a.m. |
Created at: April 9, 2026, 9:40 p.m.