Triple
T6455541
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Funeral |
E141984
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | T-Minus |
E180775
|
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: T-Minus | Statement: [Funeral, producer, T-Minus]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: T-Minus Context triple: [Funeral, producer, T-Minus]
-
A.
T-Minus
chosen
T-Minus is a Canadian record producer known for crafting melodic, atmospheric hip-hop and R&B beats for top artists like Drake, Kendrick Lamar, and J. Cole.
-
B.
Rocket Jockey
Rocket Jockey is a classic mid-20th-century young adult science fiction novel by Lester del Rey, centered on high-speed rocket racing and adventure in the Solar System.
-
C.
Zero G
Zero G is a roller coaster attraction located at Beech Bend Park in Kentucky.
-
D.
Tetro
Tetro is a 2009 drama film directed by Francis Ford Coppola, in which Maribel Verdú plays a key supporting role in a story about fractured family relationships and artistic rivalry in Buenos Aires.
-
E.
Chasing Rockets
"Chasing Rockets" is an instrumental cue from John Williams’ iconic 1978 Superman film score, accompanying one of the movie’s energetic action sequences.
- 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_69c008d2f91c8190a8178767a35e08fc |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c069d4d588819090e8a56c46c0bfe9 |
completed | March 22, 2026, 10:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bdc4e808190a7c24b963ab0aa30 |
completed | March 27, 2026, 9:20 a.m. |
Created at: March 22, 2026, 4:48 p.m.