Triple
T2832577
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irwin Winkler |
E62273
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Irwin |
E113130
|
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: Irwin | Statement: [Irwin Winkler, givenName, Irwin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Irwin Context triple: [Irwin Winkler, givenName, Irwin]
-
A.
Irwin
chosen
Irwin is a masculine given name and surname of English origin, historically associated with various notable figures in fields such as entertainment, science, and politics.
-
B.
Irvin
Irvin is a surname most prominently associated with former NFL wide receiver and sports commentator Michael Irvin.
-
C.
Darvin
Darvin is a masculine given name most notably borne by former NBA player and current basketball coach Darvin Ham.
-
D.
Milhous
Milhous is the distinctive middle name of Richard Nixon, the 37th president of the United States.
-
E.
Arvin
Arvin is a small agricultural city in Southern California’s San Joaquin Valley, known for its farming economy and diverse rural community.
- 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_69ab4c3c39188190955b9c49d98463d8 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdebe95188190bf65fb4cd88e2ec5 |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afe8bb92b08190b1de7e6973d96301 |
completed | March 10, 2026, 9:47 a.m. |
Created at: March 6, 2026, 10:01 p.m.