Triple
T21677557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Western All-Stars |
E535012
|
entity |
| Predicate | scoringRecordContext |
P145416
|
FINISHED |
| Object | features many high-scoring games |
—
|
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: features many high-scoring games | Statement: [Western All-Stars, scoringRecordContext, features many high-scoring games]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoringRecordContext Context triple: [Western All-Stars, scoringRecordContext, features many high-scoring games]
-
A.
scoringRecord
Indicates that there exists a record documenting a scoring event or outcome associated with the given entities.
-
B.
scoring
Indicates the act of achieving points or a measurable result, typically by successfully completing an action that contributes to a score or outcome.
-
C.
scoringUnit
Indicates that one entity functions as a unit or component responsible for scoring or assigning scores to another entity.
-
D.
hasScoreRecord
Indicates that an entity is associated with a specific score entry or scoring record.
-
E.
scoringDetail
Indicates a detailed breakdown of how a score was derived, including specific components, criteria, or events contributing to the overall score.
- 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_69e0c46898008190aa618a4af55bd1ee |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef8a11088081908911af2629f54c1c |
completed | April 27, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69e6968abfdc81909cf9e0bd72db9eca |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:42 p.m.