Triple
T22947034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Island Stallion |
E569901
|
entity |
| Predicate | hasFictionalHorse |
P55479
|
FINISHED |
| Object | Flame |
—
|
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: Flame | Statement: [The Island Stallion, hasFictionalHorse, Flame]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalHorse Context triple: [The Island Stallion, hasFictionalHorse, Flame]
-
A.
hasFictionalPet
Indicates that an entity has, owns, or is associated with a pet that is fictional or imaginary.
-
B.
hasRacehorseCharacter
Indicates that one entity possesses the traits, qualities, or behavioral characteristics associated with a racehorse in relation to another entity or context.
-
C.
hasNotableHorse
chosen
Indicates that an entity is associated with a horse that is considered notable or distinguished in some recognized way.
-
D.
hasFictionalAgriculturalCharacter
Indicates that an entity features or includes a character associated with agriculture within a fictional context.
-
E.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary 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.