Triple
T29322007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duel on Mustafar |
E743538
|
entity |
| Predicate | hasScoreCue |
P180524
|
FINISHED |
| Object | "Battle of the Heroes" |
—
|
NE NERFINISHED |
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: "Battle of the Heroes" | Statement: [Duel on Mustafar, hasScoreCue, "Battle of the Heroes"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScoreCue Context triple: [Duel on Mustafar, hasScoreCue, "Battle of the Heroes"]
-
A.
hasScoreRecord
Indicates that an entity is associated with a specific score entry or scoring record.
-
B.
isScoreFor
Indicates that one value represents the score or result associated with a particular entity, event, or performance.
-
C.
hasScoreCharacteristic
Indicates that one entity possesses or is associated with a particular scoring-related characteristic or property.
-
D.
hasScorer
Indicates that one entity serves as the scorer (e.g., the one who scores points, goals, or evaluations) in relation to another entity.
-
E.
hasScoreType
Indicates that an entity is associated with a particular type or category of score.
- F. None of above. chosen
Provenance (4 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_69f09125f784819080f4e9fce9fe624f |
completed | April 28, 2026, 10:51 a.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: April 28, 2026, 1:23 p.m.