Triple
T7218235
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Representatives of Cyprus |
E150189
|
entity |
| Predicate | hasAdditionalReservedSeats |
P9399
|
FINISHED |
| Object | 24 |
—
|
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: 24 | Statement: [House of Representatives of Cyprus, hasAdditionalReservedSeats, 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdditionalReservedSeats Context triple: [House of Representatives of Cyprus, hasAdditionalReservedSeats, 24]
-
A.
hasReservedSeats
chosen
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
B.
hasSeatStatus
Indicates the current condition or availability state of a seat in a given context.
-
C.
hasPrioritySeating
Indicates that one entity provides or designates reserved or preferential seating for another entity.
-
D.
hasGeneralSeats
Indicates that an entity possesses or includes general (non-reserved) seats in a seating or allocation context.
-
E.
individualSeats
Indicates that an entity provides or consists of separate, single-person seating positions rather than shared or bench-style seating.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e99170d88190b1aef326a7d81134 |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e75f84e481909e7866186ae80cff |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:53 p.m.