Triple
T1269341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quentin Tarantino |
E15673
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Quentin |
E138209
|
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: Quentin | Statement: [Quentin Tarantino, givenName, Quentin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Quentin Context triple: [Quentin Tarantino, givenName, Quentin]
-
A.
Quentin
chosen
Quentin is a fictional character appearing in the post-apocalyptic virtual reality shooter game "After the Fall."
-
B.
Terrence
Terrence is a masculine given name, commonly used in English-speaking countries and often shortened to "Terry."
-
C.
Terrence
Terrence is the given first name of Terry Francona, a prominent American Major League Baseball manager and former player.
-
D.
Terrence
Terrence is the first name of Pusha T, an American rapper, songwriter, and record executive known for his sharp lyricism and work as half of the duo Clipse.
-
E.
Will Parker
Will Parker is a cheerful, somewhat naive cowboy and rodeo performer who provides comic relief and romantic subplots in the classic Rodgers and Hammerstein musical "Oklahoma!".
- 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_69a4935a94308190bb92555b79032824 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4c03aaa8c8190bacb7de5a38329da |
completed | March 1, 2026, 10:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac99898bdc8190bbbe28083b4a548b |
completed | March 7, 2026, 9:32 p.m. |
Created at: March 1, 2026, 7:50 p.m.