Triple
T9209247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Kahn |
E221068
|
entity |
| Predicate | directed |
P7373
|
FINISHED |
| Object | Torque |
E785245
|
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: Torque | Statement: [Joseph Kahn, directed, Torque]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Torque Context triple: [Joseph Kahn, directed, Torque]
-
A.
Torque
Torque is a Uruguayan professional football club, officially known as Club Atlético Torque, that competes in the country’s league system.
-
B.
Torque
chosen
Torque is a 2004 American action film directed by Joseph Kahn that centers on high-speed motorcycle gangs, stylized stunts, and over-the-top visual flair.
-
C.
Traction
Traction is the common nickname for the Citroën Traction Avant, a pioneering French automobile famous for its early use of front-wheel drive and unitary body construction.
-
D.
Thrust
Thrust is a C++ template library for CUDA that provides high-level parallel algorithms and data structures to simplify GPU programming.
-
E.
Loop Drive
Loop Drive is the main circular roadway in New York City's Central Park used by pedestrians, cyclists, and vehicles for recreation and transit.
- 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_69ca83e9d0e081908bdb71097201a06c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccd9b3c8c081909a688ce699928fc0 |
completed | April 1, 2026, 8:39 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d077875eac8190a020dfa38998385e |
completed | April 4, 2026, 2:29 a.m. |
Created at: March 30, 2026, 7:26 p.m.