Triple
T3111711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uttar Pradesh Legislative Assembly |
E64965
|
entity |
| Predicate | seatsForScheduledCastes |
P46006
|
FINISHED |
| Object | 84 |
—
|
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: 84 | Statement: [Uttar Pradesh Legislative Assembly, seatsForScheduledCastes, 84]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatsForScheduledCastes Context triple: [Uttar Pradesh Legislative Assembly, seatsForScheduledCastes, 84]
-
A.
seatsForParty
Indicates that a seating arrangement or capacity is designated to accommodate a specific party or group.
-
B.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
C.
hasGeneralSeats
Indicates that an entity possesses or includes general (non-reserved) seats in a seating or allocation context.
-
D.
hasReservedSeats
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
E.
seatSelectionPolicy
Indicates the rules or constraints governing how seats are chosen or assigned 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada43b0b3c8190a828c9cfcf730ed9 |
completed | March 8, 2026, 4:30 p.m. |
| PD | Predicate disambiguation | batch_69ad9df25d4c81908ff0f6cff55d0563 |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:04 p.m.