Triple
T9480296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kagan |
E228617
|
entity |
| Predicate | isRelatedTo |
P37
|
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: [Kagan, isRelatedTo, Cohen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cohen Context triple: [Kagan, isRelatedTo, Cohen]
-
A.
Cohen
chosen
Cohen is a common Jewish surname of Hebrew origin historically associated with priestly lineage.
-
B.
Cohn
Cohn is a surname most prominently associated with Harry Cohn, the influential co-founder and longtime head of Columbia Pictures.
-
C.
Cohen-Kagan
Cohen-Kagan is a Hebrew-language surname most notably borne by Israeli politician and women's rights activist Rachel Cohen-Kagan.
-
D.
Jake Cohen
Jake Cohen is known primarily as the son of Michael Cohen, the former personal attorney to Donald Trump.
-
E.
Alan Cohen
Alan Cohen, better known by his professional name Corey Allen, was an American actor and director recognized for his role in "Rebel Without a Cause" and his later work directing numerous television series.
- 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_69ca84730a5081908de282651019bf2f |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd8016813881908dafc026779c89c4 |
completed | April 1, 2026, 8:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d139f261248190b8e3238f7618191d |
completed | April 4, 2026, 4:18 p.m. |
Created at: March 30, 2026, 7:54 p.m.