Triple
T11725407
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tallahassee City Commissioner, Seat 3 |
E278751
|
entity |
| Predicate | hasSeatNumberingScheme |
P21980
|
FINISHED |
| Object | numbered commission seats |
—
|
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: numbered commission seats | Statement: [Tallahassee City Commissioner, Seat 3, hasSeatNumberingScheme, numbered commission seats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatNumberingScheme Context triple: [Tallahassee City Commissioner, Seat 3, hasSeatNumberingScheme, numbered commission seats]
-
A.
seatNotationSystem
chosen
Indicates the system or convention used to label, number, or otherwise denote seats within a venue or vehicle.
-
B.
seatNumber
Indicates the specific numbered position assigned to a seat within a defined seating arrangement or venue.
-
C.
hasCabinetNumberingSystem
Indicates that there is a specific scheme or method used to assign and organize identification numbers to cabinets.
-
D.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
E.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for 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_69d6aaffec6881908bead509e8621742 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4d603cc8190b2e68d0bdd793362 |
completed | April 10, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69d88a7f51248190bf492bd7509b5413 |
completed | April 10, 2026, 5:28 a.m. |
Created at: April 8, 2026, 9:41 p.m.