Triple
T2578191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acerbo Law |
E57025
|
entity |
| Predicate | remainingSeatsAllocation |
P40374
|
FINISHED |
| Object | one-third of seats distributed proportionally among other lists |
—
|
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: one-third of seats distributed proportionally among other lists | Statement: [Acerbo Law, remainingSeatsAllocation, one-third of seats distributed proportionally among other lists]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: remainingSeatsAllocation Context triple: [Acerbo Law, remainingSeatsAllocation, one-third of seats distributed proportionally among other lists]
-
A.
hasReservedSeats
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
B.
seatsForParty
Indicates that a seating arrangement or capacity is designated to accommodate a specific party or group.
-
C.
seatNotationSystem
Indicates the system or convention used to label, number, or otherwise denote seats within a venue or vehicle.
-
D.
numberOfSeatingRows
Indicates the total count of seating rows associated with an entity, such as a venue, vehicle, or seating area.
-
E.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other in a given context.
- F. None of above. chosen
Provenance (4 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a86f9881908df29a7caaf9a7df |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0cfeae08190aed03866ba071c5c |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd209d934819093600889af9104c3 |
completed | March 7, 2026, 7:21 a.m. |
Created at: March 6, 2026, 9:49 p.m.