Triple
T29078864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fast & Furious (2009 film) |
E733916
|
entity |
| Predicate | hasSequelNumberInFranchise |
P16630
|
FINISHED |
| Object | 4 |
—
|
LITERAL 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: 4 | Statement: [Fast & Furious (2009 film), hasSequelNumberInFranchise, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSequelNumberInFranchise Context triple: [Fast & Furious (2009 film), hasSequelNumberInFranchise, 4]
-
A.
hasSequelNumber
chosen
Indicates that an entity is followed by another work in a series identified by a specific sequential number.
-
B.
hasSequel
Indicates that one work is followed by another work that continues its story, timeline, or thematic development.
-
C.
hasSequelInCanon
Indicates that a work has a subsequent work that continues its story within the officially recognized continuity.
-
D.
hasSequelDepiction
Indicates that one depiction of something is followed by another depiction that continues its story or sequence.
-
E.
hasSequelPiece
Indicates that one creative work is a subsequent installment or continuation that follows another work in a series.
- F. None of above.
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_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69fde9fc184c8190bebef35df0e76076 |
completed | May 8, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69fde6e5beb4819094945a695e961d88 |
completed | May 8, 2026, 1:36 p.m. |
Created at: April 28, 2026, 10:52 a.m.