Triple
T18837819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2023 Madhya Pradesh Legislative Assembly election |
E460709
|
entity |
| Predicate | party2SeatsBefore |
P54210
|
FINISHED |
| Object | 96 |
—
|
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: 96 | Statement: [2023 Madhya Pradesh Legislative Assembly election, party2SeatsBefore, 96]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: party2SeatsBefore Context triple: [2023 Madhya Pradesh Legislative Assembly election, party2SeatsBefore, 96]
-
A.
party2Seats
Indicates the number of seats held or allocated to the second party in a given context (such as an election or governing body).
-
B.
party1Seats
Indicates the number of seats held or allocated to the first party in a multi-party context.
-
C.
seatsForParty
Indicates that a seating arrangement or capacity is designated to accommodate a specific party or group.
-
D.
secondPartySeats
Indicates that a second party assigns or provides seating or seats to another entity.
-
E.
previousNumberOfSeats
chosen
Indicates the number of seats an entity had before a change or update in its seating count.
- 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.