Triple
T15958792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Anderton |
E387003
|
entity |
| Predicate | motivationInFilm |
P91485
|
FINISHED |
| Object | clear his name |
—
|
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: clear his name | Statement: [John Anderton, motivationInFilm, clear his name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: motivationInFilm Context triple: [John Anderton, motivationInFilm, clear his name]
-
A.
motivationFor
Indicates that one entity serves as the reason, drive, or incentive behind another entity’s action, state, or occurrence.
-
B.
characterMotivation
chosen
Indicates the underlying reasons, desires, or goals that drive a character’s actions and decisions within a narrative.
-
C.
motivatedByGoal
Indicates that an action, behavior, or state occurs as a result of an intention to achieve a specific goal or desired outcome.
-
D.
workInspiredFilm
Indicates that a particular work (such as a book, article, or other creation) served as the inspiration or source material for a film.
-
E.
laterMotivation
Indicates that one event, state, or action serves as a motivation or reason for another event, state, or action that occurs later in time.
- 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_69d86da882448190a82ea962fe343b79 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e173b3bf6c81909230170e833d7ce7 |
completed | April 16, 2026, 11:41 p.m. |
| PD | Predicate disambiguation | batch_69e142d6fb588190b4176eab4bbae774 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:53 a.m.