Triple
T3998899
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Francisco Bay Area Rapid Transit District |
E87163
|
entity |
| Predicate | hasNumberOfBoardMembers |
P3128
|
FINISHED |
| Object | 9 |
—
|
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: 9 | Statement: [San Francisco Bay Area Rapid Transit District, hasNumberOfBoardMembers, 9]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfBoardMembers Context triple: [San Francisco Bay Area Rapid Transit District, hasNumberOfBoardMembers, 9]
-
A.
numberOfBoardMembers
chosen
Indicates the total count of individuals who serve as members on a board.
-
B.
hasNumberOfVotingMembers
Indicates the specific count of individuals who hold voting rights within a given group or body.
-
C.
hasMembers
Indicates that a group, organization, or collection includes certain entities as its members.
-
D.
hasPermanentMembers
Indicates that certain members of a group or organization hold ongoing, non-temporary membership status.
-
E.
numberOfAppointedMembers
Indicates the specific count of members who have been formally appointed to a group, body, or position.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa8579288190940487ad07e38de0 |
completed | March 9, 2026, 4:51 p.m. |
| PD | Predicate disambiguation | batch_69aef8f89f2881909b0965419d15d46c |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.