Triple
T6081908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vivienne Michel |
E135542
|
entity |
| Predicate | narratesEventsUpTo |
P60472
|
FINISHED |
| Object | arrival of James Bond |
—
|
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: arrival of James Bond | Statement: [Vivienne Michel, narratesEventsUpTo, arrival of James Bond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: narratesEventsUpTo Context triple: [Vivienne Michel, narratesEventsUpTo, arrival of James Bond]
-
A.
basedOnEventsDescribedIn
Indicates that something is derived from, inspired by, or constructed using the events described in another source.
-
B.
narratesPortionsOf
chosen
Indicates that one entity recounts, tells, or provides a narrative of specific parts or segments of another entity.
-
C.
notableEventCoverage
Indicates that there is media or documented coverage specifically focused on a notable event related to the subject.
-
D.
chronologicallyCovers
Indicates that one time period, event, or sequence extends over and includes the entire chronological span of another.
-
E.
narratedTo
Indicates that one entity tells or recounts a story, event, or information directly to another entity as the audience.
- 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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05774bc948190a446b27e83f7079b |
completed | March 22, 2026, 8:56 p.m. |
| PD | Predicate disambiguation | batch_69c049f21fe08190995df3c5c05fb8ea |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:11 p.m.