Triple
T33608637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1988 United States Senate elections |
E860925
|
entity |
| Predicate | beforeParty2Seats |
P128078
|
FINISHED |
| Object | 45 |
—
|
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: 45 | Statement: [1988 United States Senate elections, beforeParty2Seats, 45]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: beforeParty2Seats Context triple: [1988 United States Senate elections, beforeParty2Seats, 45]
-
A.
beforeParty1Seats
Indicates that one entity takes its seat or is seated before another party (Party1) takes theirs.
-
B.
party2Seats
chosen
Indicates the number of seats held or allocated to the second party in a given context (such as an election or governing body).
-
C.
party1Seats
Indicates the number of seats held or allocated to the first party in a multi-party context.
-
D.
secondPartySeats
Indicates that a second party assigns or provides seating or seats to another entity.
-
E.
seatsForParty
Indicates that a seating arrangement or capacity is designated to accommodate a specific party or group.
- 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_69f3498037c88190a4500f002b5540e0 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:41 a.m.