Triple
T12877330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Face/Off |
E308001
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Terence Chang |
E237864
|
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: Terence Chang | Statement: [Face/Off, producer, Terence Chang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Terence Chang Context triple: [Face/Off, producer, Terence Chang]
-
A.
Terence Chang
chosen
Terence Chang is a Hong Kong-born film producer best known for his collaborations with director John Woo on action films in both Asian and Hollywood cinema.
-
B.
Terence Yin
Terence Yin is a Hong Kong-based actor and singer known for his supporting roles in action and crime films across Hong Kong and mainland Chinese cinema.
-
C.
Carlisle Chang
Carlisle Chang was a prominent Trinidadian artist and designer best known for his influential contributions to national symbols and public art in Trinidad and Tobago.
-
D.
Ben Chang
Ben Chang is a chaotic and eccentric Spanish teacher-turned-student from the TV sitcom "Community," known for his unpredictable behavior and over-the-top antics.
-
E.
Terry Chen
Terry Chen is a Canadian actor known for his roles in films like "Snakes on a Plane" and various television series.
- 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_69d7bdf69bc48190af6c2621f28ca351 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d970fa8474819086a8af3c90f3ca84 |
completed | April 10, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f69bb83bac8190838f7537b806317c |
completed | May 3, 2026, 12:50 a.m. |
Created at: April 9, 2026, 5:38 p.m.