Triple
T20406189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iranian parliamentary elections |
E500473
|
entity |
| Predicate | reservedSeatsCount |
P9399
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [Iranian parliamentary elections, reservedSeatsCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reservedSeatsCount Context triple: [Iranian parliamentary elections, reservedSeatsCount, 5]
-
A.
hasReservedSeats
chosen
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
B.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
-
C.
seatCount
Indicates the number of seats associated with an entity, such as a venue, vehicle, or room.
-
D.
currentNumberOfSeats
Indicates the present total count of seats associated with an entity or context.
-
E.
definesNumberOfSeats
Indicates that an entity specifies or determines the total number of seats associated with another entity.
- 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_69e0b4a81bec8190b69adfdc1336a015 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67992cfb88190ae49a1723e6667a1 |
completed | April 20, 2026, 7:08 p.m. |
| PD | Predicate disambiguation | batch_69e5765d7cb48190adec18d6d1e3d263 |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 16, 2026, 11:29 a.m.