Triple
T12101830
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spanish Riding School |
E288207
|
entity |
| Predicate | hasGenderPolicyForHorses |
P15554
|
FINISHED |
| Object | stallions only |
—
|
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: stallions only | Statement: [Spanish Riding School, hasGenderPolicyForHorses, stallions only]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGenderPolicyForHorses Context triple: [Spanish Riding School, hasGenderPolicyForHorses, stallions only]
-
A.
hasGenderPolicy
Indicates that an entity has adopted, implemented, or is governed by a specific policy related to gender issues or gender equality.
-
B.
usesHorseType
Indicates that one entity employs, relies on, or operates using a specific type or category of horse.
-
C.
hasGenderSystem
Indicates that an entity employs or is characterized by a particular system for categorizing gender.
-
D.
hasGenderRequirement
chosen
Indicates that a particular role, activity, or context specifies a required or restricted gender for participation or eligibility.
-
E.
governsGender
Indicates that one entity determines or constrains the gender classification or gender-related properties of another entity.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9178ad99c8190a54777b9bbe998bc |
completed | April 10, 2026, 3:30 p.m. |
| PD | Predicate disambiguation | batch_69d915000454819089fee00022055599 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:48 p.m.