Triple
T506320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Division |
E10508
|
entity |
| Predicate | teamCountType |
P14505
|
FINISHED |
| Object | fixed membership |
—
|
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: fixed membership | Statement: [Metropolitan Division, teamCountType, fixed membership]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamCountType Context triple: [Metropolitan Division, teamCountType, fixed membership]
-
A.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
B.
typeOfTeams
Indicates the categories or kinds of teams to which an entity or group of entities belongs.
-
C.
typicalTeamSize
Indicates the usual or most common number of members that make up a given team.
-
D.
typicalNumberOfCWSTeams
Indicates the usual or standard number of CWS teams associated with or involved in a given context or entity.
-
E.
teamCodeType
Indicates the classification or category type associated with a particular team code.
- 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_69a2e848adf881908e5e04f7af030093 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f14c83f08190b1028f4929866db4 |
completed | Feb. 28, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69a2edfce7a08190a408bc019de60d5d |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebbd70481908b462296671de67b |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.