Triple
T1063088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boeing 757 |
E22949
|
entity |
| Predicate | numberOfExits |
P9845
|
FINISHED |
| Object | up to 8 main cabin doors |
—
|
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: up to 8 main cabin doors | Statement: [Boeing 757, numberOfExits, up to 8 main cabin doors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfExits Context triple: [Boeing 757, numberOfExits, up to 8 main cabin doors]
-
A.
hasNumberOfEntrances
chosen
Indicates the relationship that specifies how many entrances an entity possesses.
-
B.
numberOfGates
Indicates the quantity of gates associated with or belonging to an entity.
-
C.
numberOfCorridors
Indicates the total count of corridors associated with or contained within a given entity or structure.
-
D.
hasSeparateEntrances
Indicates that the related entities each have their own distinct entrance, rather than sharing a common one.
-
E.
numberOfTerminals
Indicates the total count of terminal points or endpoints associated with an 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_69a493dada0481909c43649f9843ea91 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b8f68a54819084326d87c3498252 |
completed | March 1, 2026, 10:08 p.m. |
| PD | Predicate disambiguation | batch_69a4b7359eb881909c868a558861cc18 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.