Triple
T5077031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abby Joseph Cohen |
E114422
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Abby Joseph Cohen |
E114422
|
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: Abby Joseph Cohen | Statement: [Abby Joseph Cohen, name, Abby Joseph Cohen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abby Joseph Cohen Context triple: [Abby Joseph Cohen, name, Abby Joseph Cohen]
-
A.
Abby Joseph Cohen
chosen
Abby Joseph Cohen is an American economist and former Goldman Sachs partner renowned for her influential stock market forecasts and commentary on U.S. equity markets.
-
B.
Robyn Cohen
Robyn Cohen is an American actress best known for her role in Wes Anderson’s film "The Life Aquatic with Steve Zissou."
-
C.
Rachel Cohen-Kagan
Rachel Cohen-Kagan was an Israeli politician, women's rights activist, and one of the signatories of Israel's Declaration of Independence.
-
D.
June Cohen
June Cohen is a media entrepreneur and former TED executive best known for co-founding the business podcast and learning platform "Masters of Scale."
-
E.
Basya Cohen
Basya Cohen, better known as Betty Comden, was an American lyricist, screenwriter, and performer famed for her influential work on classic Broadway musicals and Hollywood films.
- 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_69bd443dbf908190a9401e9c2dc7bd7d |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd74d3b0088190a658864cb120eef4 |
completed | March 20, 2026, 4:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69beb12718388190974df282ec2c6a11 |
completed | March 21, 2026, 2:54 p.m. |
Created at: March 20, 2026, 1:39 p.m.