Triple
T3534829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States Senate elections |
E74745
|
entity |
| Predicate | classesOfSeats |
P48161
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [United States Senate elections, classesOfSeats, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classesOfSeats Context triple: [United States Senate elections, classesOfSeats, 3]
-
A.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
B.
hasGeneralSeats
Indicates that an entity possesses or includes general (non-reserved) seats in a seating or allocation context.
-
C.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
D.
ticketClass
Indicates the category or level of service assigned to a ticket within a ticketing or reservation system.
-
E.
seatNumber
Indicates the specific numbered position assigned to a seat within a defined seating arrangement or venue.
- 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_69ad85d1a3948190931fd1ea1f49717b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc9cff5c81909011f34c9bf28e11 |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae13ab808190a5d6ecdc7543445e |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed7f2ec819085467d281712e0e8 |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:19 p.m.