Triple
T33238654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | House of Representatives (New Zealand) |
E850903
|
entity |
| Predicate | canHaveOverhangSeats |
P176237
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [House of Representatives (New Zealand), canHaveOverhangSeats, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canHaveOverhangSeats Context triple: [House of Representatives (New Zealand), canHaveOverhangSeats, true]
-
A.
hasReservedSeats
Indicates that specific seats have been set aside or allocated in advance for a particular entity or purpose.
-
B.
hasFlexibleSeating
Indicates that an entity provides seating arrangements that can be easily rearranged, adjusted, or reconfigured to suit different uses or preferences.
-
C.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
D.
hasTemporarySeatingCapacity
Indicates the number of seats that can be added or arranged temporarily for an entity, beyond its permanent seating capacity.
-
E.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
- 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_69f349613f988190a1eb75467d167122 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
| PDg | Predicate description generation | batch_69f6dd3b335481909e24d4eb5b0269f9 |
completed | May 3, 2026, 5:29 a.m. |
Created at: May 1, 2026, 1:31 a.m.