Triple
T7031696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NBA Summer League |
E163284
|
entity |
| Predicate | typicalTeamCount |
P6986
|
FINISHED |
| Object | 30 NBA teams participate in Las Vegas segment |
—
|
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: 30 NBA teams participate in Las Vegas segment | Statement: [NBA Summer League, typicalTeamCount, 30 NBA teams participate in Las Vegas segment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTeamCount Context triple: [NBA Summer League, typicalTeamCount, 30 NBA teams participate in Las Vegas segment]
-
A.
typicalTeamSize
Indicates the usual or most common number of members that make up a given team.
-
B.
teamCountType
Indicates how the number of teams is categorized or measured within a given context.
-
C.
hasNumberOfTeams
chosen
Indicates the quantity of teams associated with or contained by a given entity.
-
D.
typicalNumberOfCWSTeams
Indicates the usual or standard number of CWS teams associated with or involved in a given context or entity.
-
E.
typicalNumberOfTopDivisionTeams
Indicates the usual or standard number of teams that compete in the highest-level division of a league or competition.
- 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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e458ad9c81908c3f492b317ce291 |
completed | March 27, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69c6e1b9a2488190aea351d96afa5a12 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:36 p.m.