Triple
T4967222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Egyptian parliamentary elections, 2011–2012 |
E111557
|
entity |
| Predicate | individualSeats |
P61488
|
FINISHED |
| Object | 166 |
—
|
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: 166 | Statement: [Egyptian parliamentary elections, 2011–2012, individualSeats, 166]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: individualSeats Context triple: [Egyptian parliamentary elections, 2011–2012, individualSeats, 166]
-
A.
classesOfSeats
Indicates the different categories or types of seats associated with something, such as a venue, vehicle, or event.
-
B.
currentNumberOfSeats
Indicates the present total count of seats associated with an entity or context.
-
C.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
-
D.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
E.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other 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_69bd4419393c819086319a6fe4bf8542 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd72e49b048190bac55d9e7a6f7963 |
completed | March 20, 2026, 4:16 p.m. |
| PD | Predicate disambiguation | batch_69bd71447fe88190bb62c5e8753da7a7 |
completed | March 20, 2026, 4:09 p.m. |
| PDg | Predicate description generation | batch_69bd72e1b7cc8190b2e621fdf8f22e38 |
completed | March 20, 2026, 4:16 p.m. |
Created at: March 20, 2026, 1:32 p.m.