Triple
T20720629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bennett S. LeBow |
E509299
|
entity |
| Predicate | hasGivenName |
P17
|
FINISHED |
| Object | Bennett |
—
|
NE NERFINISHED |
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: Bennett | Statement: [Bennett S. LeBow, hasGivenName, Bennett]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bennett Context triple: [Bennett S. LeBow, hasGivenName, Bennett]
-
A.
Bennett
chosen
Bennett is a common English-language surname of Anglo-Norman origin borne by numerous notable individuals across politics, arts, and sciences.
-
B.
Bennett
Bennett is the main villain and former comrade-turned-mercenary antagonist who battles Arnold Schwarzenegger’s character in the 1985 action film "Commando."
-
C.
Bennett
Bennett is a fictional character from the action film "Desert Saints."
-
D.
Bennett Brien
Bennett Brien is a Native American artist and designer best known for creating the University of North Dakota’s former Fighting Sioux logo.
-
E.
Bennett Holiday
Bennett Holiday is a young, ambitious Washington lawyer in the geopolitical thriller film "Syriana," navigating corruption and power struggles in the oil industry.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c4cc648190b45fda6e2b20af56 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1d5eec08190832ffba8a90f3076 |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:26 p.m.