Triple
T260882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sam Jones |
E5537
|
entity |
| Predicate | competitionClass |
P10053
|
FINISHED |
| Object | professional basketball |
—
|
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: professional basketball | Statement: [Sam Jones, competitionClass, professional basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: competitionClass Context triple: [Sam Jones, competitionClass, professional basketball]
-
A.
typeOfCompetition
Indicates the specific kind or category of competition in which an entity participates or is involved.
-
B.
competitionLevel
Indicates the degree or intensity of competitive pressure or rivalry present in a given context or interaction.
-
C.
competition
Indicates a relationship where two or more entities strive against each other to achieve a superior outcome, advantage, or reward.
-
D.
competitionFormat
Indicates the specific structure or ruleset under which a competition is organized and conducted.
-
E.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
- 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_69a2580a64ac8190ad76e34bb0715b5e |
completed | Feb. 28, 2026, 2:50 a.m. |
| NER | Named-entity recognition | batch_69a25e2aba74819093eddd8d820260c0 |
completed | Feb. 28, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69a25b6c968c819094fc903a3a377e15 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25e292fdc8190bfd51d8848f9ed58 |
completed | Feb. 28, 2026, 3:16 a.m. |
Created at: Feb. 28, 2026, 2:55 a.m.