Triple
T30667726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Consuelo (West Side Story) |
E780707
|
entity |
| Predicate | relationshipToSharks |
P204172
|
FINISHED |
| Object | supporter |
—
|
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: supporter | Statement: [Consuelo (West Side Story), relationshipToSharks, supporter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationshipToSharks Context triple: [Consuelo (West Side Story), relationshipToSharks, supporter]
-
A.
relationshipToCreature
Indicates a specified type of relational connection that one entity has toward a particular creature.
-
B.
hasSharkAntagonist
Indicates that an entity features a shark serving as an opposing or hostile force, often in a central conflict role.
-
C.
relationshipToSponges
Indicates the type or nature of a relationship that entities have with sponges.
-
D.
relationshipToDory
Indicates the specific type of relationship or connection that one entity has to Dory.
-
E.
relationshipToMariner
Indicates the specific familial, social, or professional connection that an entity has to a mariner.
- 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_69f224a6d10481909290be1a00fc83b3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a0340784c488190aa6c7c9be2e8a434 |
completed | May 12, 2026, 3 p.m. |
| PD | Predicate disambiguation | batch_6a033f33eddc819091507716f6ed7d7d |
completed | May 12, 2026, 2:54 p.m. |
| PDg | Predicate description generation | batch_6a0340777e70819083746599841c8fe5 |
completed | May 12, 2026, 3 p.m. |
Created at: April 29, 2026, 8:31 p.m.