Triple
T37785409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sioux City Council Chambers |
E941940
|
entity |
| Predicate | hasTypeOfMeeting |
P3082
|
FINISHED |
| Object | legislative sessions |
—
|
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: legislative sessions | Statement: [Sioux City Council Chambers, hasTypeOfMeeting, legislative sessions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfMeeting Context triple: [Sioux City Council Chambers, hasTypeOfMeeting, legislative sessions]
-
A.
hasMeeting
Indicates that one entity is scheduled to participate in or hold a meeting with another entity or at a specific time or place.
-
B.
hasConferenceType
Indicates that an entity is associated with or classified by a specific type or category of conference.
-
C.
hasPrimaryMeeting
Indicates that an entity is associated with its main or most important meeting, distinguishing it from other meetings it may have.
-
D.
meetingType
chosen
Indicates the specific category or format of a meeting that characterizes how it is organized or conducted.
-
E.
hasMeetingPlaceType
Indicates the specific type or category of place where a meeting is held or intended to occur.
- 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_69f76ee5cb0c81909a363d1c929156c0 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fff86e544c81908063f61b876c9d78 |
completed | May 10, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fff7e7cb688190977eeca41aad25b9 |
completed | May 10, 2026, 3:13 a.m. |
Created at: May 3, 2026, 4:19 p.m.