Triple
T20532908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tarrant County Commissioners Court |
E504114
|
entity |
| Predicate | holdsRegularMeetings |
P47991
|
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: [Tarrant County Commissioners Court, holdsRegularMeetings, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: holdsRegularMeetings Context triple: [Tarrant County Commissioners Court, holdsRegularMeetings, yes]
-
A.
meetsRegularly
chosen
Indicates that two or more entities come together on a recurring or scheduled basis.
-
B.
meetingsAre
Indicates that certain entities function as or are classified as meetings in relation to one another.
-
C.
meetingsWere
Indicates that one or more meetings occurred or were held between the referenced entities.
-
D.
hasPublicMeetings
Indicates that an entity organizes or holds meetings that are open and accessible to the general public.
-
E.
convenesRegularSession
Indicates that an entity formally brings together a group or body for its routine or scheduled meeting.
- 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_69e0b4b3a6e08190ae663701f50fab8e |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a06c709881908ef0995426a58759 |
completed | April 20, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69e59fdb7ad88190924176c32a195db3 |
completed | April 20, 2026, 3:39 a.m. |
Created at: April 16, 2026, 11:37 a.m.