Triple
T6061707
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dunning-Cohen Champions Field |
E135045
|
entity |
| Predicate | namedFor |
P63
|
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: [Dunning-Cohen Champions Field, namedFor, Cohen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cohen Context triple: [Dunning-Cohen Champions Field, namedFor, 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.
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.
- 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_69c00878d06881909ee78e88913bf890 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0572100e8819084c3174921a2d527 |
completed | March 22, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d197dd08190bcc6904c7c2e41aa |
completed | March 23, 2026, 10:59 a.m. |
Created at: March 22, 2026, 4:10 p.m.