Triple
T4224246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilbur J. Cohen |
E94415
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Cohen |
E109009
|
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: Cohen | Statement: [Wilbur J. Cohen, familyName, Cohen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cohen Context triple: [Wilbur J. Cohen, familyName, Cohen]
-
A.
Cohen
chosen
Cohen is a common Jewish surname of Hebrew origin historically associated with priestly lineage.
-
B.
Cohen-Kagan
Cohen-Kagan is a Hebrew-language surname most notably borne by Israeli politician and women's rights activist Rachel Cohen-Kagan.
-
C.
Jake Cohen
Jake Cohen is known primarily as the son of Michael Cohen, the former personal attorney to Donald Trump.
-
D.
Genghis Cohen
Genghis Cohen is a minor character in Thomas Pynchon's novel "The Crying of Lot 49," known as a philatelist who helps analyze the mysterious stamps central to the story's conspiracy.
-
E.
Nat Cohen
Nat Cohen was a notable member of the British Battalion, recognized for his involvement in the International Brigades during the Spanish Civil War.
- 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_69b3453700a08190ae88792e3dc63207 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e4bf6088190926b982039a12079 |
completed | March 12, 2026, 11:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5964532e08190bb1dc56f734e6ebb |
completed | March 14, 2026, 5:09 p.m. |
Created at: March 12, 2026, 11:04 p.m.