Triple
T26116447
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Etihad First Apartments |
E658835
|
entity |
| Predicate | typicalSeatCount |
P196486
|
FINISHED |
| Object | 9 apartments per A380 |
—
|
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: 9 apartments per A380 | Statement: [Etihad First Apartments, typicalSeatCount, 9 apartments per A380]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalSeatCount Context triple: [Etihad First Apartments, typicalSeatCount, 9 apartments per A380]
-
A.
typicalSeatingCapacityUpperBound
Indicates the maximum number of seats that a venue or vehicle is typically designed or allowed to accommodate under normal conditions.
-
B.
typicalSeatingCapacityLowerBound
Indicates the minimum number of seats that an entity is typically designed or expected to provide.
-
C.
seatingCapacity
Indicates the maximum number of people that something (typically a venue or vehicle) is designed or allowed to seat.
-
D.
typicalSeat
Indicates the usual or standard seating position or location associated with an entity in a given 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. 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fe59d11e9881909d2f33b7c717030e |
completed | May 8, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69fe394fdfbc8190a931926ae3635cbf |
completed | May 8, 2026, 7:28 p.m. |
| PDg | Predicate description generation | batch_69fe59d03a648190bbe846cb5730a477 |
completed | May 8, 2026, 9:46 p.m. |
Created at: April 26, 2026, 8:05 p.m.