Triple
T3523438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tingle Creek Chase |
E74479
|
entity |
| Predicate | obstacleType |
P1950
|
FINISHED |
| Object | steeplechase fences |
—
|
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: steeplechase fences | Statement: [Tingle Creek Chase, obstacleType, steeplechase fences]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: obstacleType Context triple: [Tingle Creek Chase, obstacleType, steeplechase fences]
-
A.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
enemyType
Indicates that one entity is classified as an enemy of a specified type or category in relation to another entity.
-
C.
spurType
Indicates the specific kind or category of spur associated with or used by an entity.
-
D.
isDifficultToAccessBecauseOf
Indicates that something is hard to reach, obtain, or use due to a specified obstacle, condition, or circumstance.
-
E.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc4f16b8819094ad2755670ddc7b |
completed | March 8, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69adae121a048190b03825a001d21f49 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.