Triple
T10239326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Sharks |
E243545
|
entity |
| Predicate | playsBasketballCode |
P93146
|
FINISHED |
| Object | FIBA rules |
—
|
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: FIBA rules | Statement: [Shanghai Sharks, playsBasketballCode, FIBA rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsBasketballCode Context triple: [Shanghai Sharks, playsBasketballCode, FIBA rules]
-
A.
playsCollegeBasketballIn
Indicates that an individual is a member of and competes for a college or university’s basketball team located at a specified institution or place.
-
B.
representsInBasketball
Indicates that one entity serves as an official representative (such as an agent, delegate, or spokesperson) for another entity specifically in the context of basketball.
-
C.
hasBasketballLevel
Indicates that an entity possesses a specified level of skill, proficiency, or ranking in basketball.
-
D.
playedHighSchoolBasketballAt
Indicates that a person was a member of and participated on the basketball team of a particular high school.
-
E.
playedCollegeBasketballFor
Indicates that a person was a member of and competed for a specific college or university’s basketball team.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d328272c8190a3548d7f7f38cfc4 |
completed | April 7, 2026, 9:49 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ebd6c88190a1f3f4a72a99d6fe |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d32741888190928b045e2241cfac |
completed | April 7, 2026, 9:49 a.m. |
Created at: April 6, 2026, 11:23 a.m.