Triple
T25582647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States horse racing tracks |
E641291
|
entity |
| Predicate | typicallyFeature |
P5084
|
FINISHED |
| Object | dirt track surfaces |
—
|
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: dirt track surfaces | Statement: [United States horse racing tracks, typicallyFeature, dirt track surfaces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyFeature Context triple: [United States horse racing tracks, typicallyFeature, dirt track surfaces]
-
A.
typicalFeatures
chosen
Indicates that the related entities are characteristic or commonly occurring features or attributes of something.
-
B.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
D.
featuresText
Indicates that an entity includes or presents a specific piece of text as one of its characteristics or contents.
-
E.
specialFeatures
Indicates the distinctive or additional characteristics, functionalities, or attributes that set an entity apart from standard or typical versions.
- 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_69e75dc42b588190a98b58e0df359674 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69fd5d48855c8190bd93070b6a00d8b5 |
completed | May 8, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69fd5c9aabb88190912800d90184a89d |
completed | May 8, 2026, 3:46 a.m. |
Created at: April 21, 2026, 4:13 p.m.