Triple
T2012122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Road Hole |
E43710
|
entity |
| Predicate | teeShotMustCarry |
P34474
|
FINISHED |
| Object | Old Course Hotel property |
—
|
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: Old Course Hotel property | Statement: [Road Hole, teeShotMustCarry, Old Course Hotel property]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teeShotMustCarry Context triple: [Road Hole, teeShotMustCarry, Old Course Hotel property]
-
A.
shoots
Indicates that one entity propels a projectile or discharge toward another entity, typically with the intent to hit or affect it.
-
B.
shotType
Indicates the specific kind or category of shot used or taken in a given context (e.g., in film, photography, or sports).
-
C.
shootsCatches
Indicates that one entity shoots something that is then caught by another entity.
-
D.
capturedEquipment
Indicates that one party has taken possession of another party’s equipment, typically as a result of conflict, competition, or enforcement.
-
E.
meetsInCamera
Indicates that two or more entities are physically present together in the same camera frame or shot at the same time.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b2ed6c8190ad51f0af90db2a02 |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb83e7888819096dc40275c77daff |
completed | March 7, 2026, 5:31 a.m. |
Created at: March 4, 2026, 7:37 p.m.