Triple
T18837818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2023 Madhya Pradesh Legislative Assembly election |
E460709
|
entity |
| Predicate | party1SeatsBefore |
P128077
|
FINISHED |
| Object | 127 |
—
|
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: 127 | Statement: [2023 Madhya Pradesh Legislative Assembly election, party1SeatsBefore, 127]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: party1SeatsBefore Context triple: [2023 Madhya Pradesh Legislative Assembly election, party1SeatsBefore, 127]
-
A.
party1Seats
chosen
Indicates the number of seats held or allocated to the first party in a multi-party context.
-
B.
party2Seats
Indicates the number of seats held or allocated to the second party in a given context (such as an election or governing body).
-
C.
seatsForParty
Indicates that a seating arrangement or capacity is designated to accommodate a specific party or group.
-
D.
party6Seats
Indicates the number of seats held or allocated to a sixth party in a multi-party context.
-
E.
numberOfMembersSeated
Indicates the count of members who are currently seated in a given context or setting.
- 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a99f443881909516a82208fd0178 |
completed | April 20, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d1e7dac81909ea1e758c87773c5 |
completed | April 19, 2026, 8:06 a.m. |
Created at: April 10, 2026, 11:56 a.m.