Triple
T22946775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand the Bull |
E569894
|
entity |
| Predicate | includesBullfightScene |
P136051
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Ferdinand the Bull, includesBullfightScene, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesBullfightScene Context triple: [Ferdinand the Bull, includesBullfightScene, yes]
-
A.
hasFightSceneWith
Indicates that two entities participate together in a fight scene or combat sequence.
-
B.
hasBullring
Indicates that a location or facility possesses or contains a bullring used for bullfighting or related events.
-
C.
hasBattleScenes
chosen
Indicates that an entity (such as a work of fiction or media) contains scenes depicting battles or combat.
-
D.
containsViolence
Indicates that the subject includes, depicts, or involves acts of physical harm, aggression, or violent behavior.
-
E.
hasRomanticSceneAt
Indicates that a romantic scene occurs at a specific location or point in time within a work or context.
- 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_69e2459199d08190a8184ee2aa935842 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1819e559c81909e63acfc23f9476b |
completed | April 29, 2026, 3:57 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:46 p.m.