Triple
T15405568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loma Alta Park |
E368442
|
entity |
| Predicate | hasTypeOfSportFacility |
P25287
|
FINISHED |
| Object | basketball courts |
—
|
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: basketball courts | Statement: [Loma Alta Park, hasTypeOfSportFacility, basketball courts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfSportFacility Context triple: [Loma Alta Park, hasTypeOfSportFacility, basketball courts]
-
A.
hasSportsVenueType
chosen
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
-
B.
hasFacilityType
Indicates that an entity possesses or is associated with a specific type or category of facility.
-
C.
isWithinSportsFacility
Indicates that one entity is located inside the boundaries of a sports facility or complex.
-
D.
designedFacilityType
Indicates the type or category of facility that something (such as a plan, system, or component) is specifically designed for.
-
E.
hasCulturalFacilityType
Indicates that an entity has or is associated with a specific type of cultural facility (such as a museum, theater, or gallery).
- 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8fde64819082ec0c68df305561 |
completed | April 16, 2026, 1:42 a.m. |
| PD | Predicate disambiguation | batch_69ded27b8cac8190bfa77698d53c5d1c |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:20 a.m.