Triple
T22967841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pasatiempo Golf Club |
E571097
|
entity |
| Predicate | hasScorecardUnit |
P150431
|
FINISHED |
| Object | yards |
—
|
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: yards | Statement: [Pasatiempo Golf Club, hasScorecardUnit, yards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasScorecardUnit Context triple: [Pasatiempo Golf Club, hasScorecardUnit, yards]
-
A.
scoringUnit
Indicates that one entity functions as a unit or component responsible for scoring or assigning scores to another entity.
-
B.
hasScoreRecord
Indicates that an entity is associated with a specific score entry or scoring record.
-
C.
hasScoreSystem
Indicates that an entity uses, is governed by, or is associated with a particular scoring or rating system.
-
D.
hasRankingUnit
Indicates that one entity is associated with a specific unit or scale used to express its ranking or ordered position.
-
E.
hasScoreCharacteristic
Indicates that one entity possesses or is associated with a particular scoring-related characteristic or property.
- F. None of above. chosen
Provenance (4 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_69e245b2c6548190a0e4c7f2f7df2d48 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f182301f388190bb39e3d5b356dc65 |
completed | April 29, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69ef3b9101f48190a06c69dff26c6441 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:48 p.m.