Triple
T1543953
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Westchester County Board of Legislators |
E32932
|
entity |
| Predicate | openMeetings |
P11970
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Westchester County Board of Legislators, openMeetings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: openMeetings Context triple: [Westchester County Board of Legislators, openMeetings, yes]
-
A.
openMeetingsRequirement
chosen
Indicates that certain meetings must be accessible to the public or non-participants, rather than being held in private or closed session.
-
B.
meetingType
Indicates the specific category or format of a meeting that characterizes how it is organized or conducted.
-
C.
meetingNumber
Indicates the specific numerical identifier assigned to distinguish one meeting from others.
-
D.
convenesIn
Indicates that an entity brings together or assembles a group, meeting, or event at a specific place or venue.
-
E.
convenesDuring
Indicates that one entity formally gathers or brings together another entity or group during a specified time period or event.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa95c1a2948190a2b98469afec1a7d |
completed | March 6, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69a907b2453c8190a41f6b88c8217d1e |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.