Triple
T25884336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alex English |
E652144
|
entity |
| Predicate | pointsScoredLeader |
P70197
|
FINISHED |
| Object | 1980s decade in the NBA |
—
|
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: 1980s decade in the NBA | Statement: [Alex English, pointsScoredLeader, 1980s decade in the NBA]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsScoredLeader Context triple: [Alex English, pointsScoredLeader, 1980s decade in the NBA]
-
A.
pointsLeader
chosen
Indicates that the subject entity is the current leader in points relative to other entities in a given context or competition.
-
B.
pointsScored
Indicates the number of points an entity has earned or achieved in a particular event, game, or context.
-
C.
scoringLeaderAssists
Indicates that the entity identified as the scoring leader in a game or season also recorded the most assists (or a specified number of assists) in that context.
-
D.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
-
E.
scoringLeaderGoals
Indicates that the subject is the leading scorer in terms of goals, having scored more goals than any other relevant participant in the given context.
- 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_69e7ab3b92cc81908febd90317862647 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f60340e45c819088e093e535e70022 |
completed | May 2, 2026, 1:59 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 22, 2026, 8:17 a.m.