Triple
T7930402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metro Council President |
E184174
|
entity |
| Predicate | isSeat |
P3522
|
FINISHED |
| Object | region-wide elected position |
—
|
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: region-wide elected position | Statement: [Metro Council President, isSeat, region-wide elected position]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSeat Context triple: [Metro Council President, isSeat, region-wide elected position]
-
A.
seatIs
Indicates that one entity functions as the seat or seating position of another entity.
-
B.
hasSeat
chosen
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
C.
isSafeSeatFor
Indicates that one entity is a suitable and secure seating option for another entity, posing no unacceptable risk or harm.
-
D.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
-
E.
seatOn
Indicates that one entity is positioned or placed on a seat or seating surface associated with another entity.
- 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_69ca8290c21c8190906a5ca6fe2b03c4 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3accc388819087065ebe7d5d9591 |
completed | March 31, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69cae9335f288190ba96781fd6576a2b |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 5:07 p.m.