Triple
T1721990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Airbus A300 |
E37411
|
entity |
| Predicate | originalCockpitCrew |
P26357
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Airbus A300, originalCockpitCrew, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalCockpitCrew Context triple: [Airbus A300, originalCockpitCrew, 3]
-
A.
firstCrewedTestFlightCrew
Indicates that the subject is a member of the crew on the first crewed test flight of the referenced vehicle or mission.
-
B.
crewType
Indicates the specific role or category of crew associated with an entity, such as the type of personnel assigned to operate or support it.
-
C.
crew
Indicates that one entity serves as the group of people who operate, staff, or work on another entity (such as a vehicle, vessel, or production).
-
D.
totalCrewMembers
chosen
Indicates the total number of crew members associated with a given entity or context.
-
E.
crewInvolvedIn
Indicates that a crew (as a group or unit) participates in, contributes to, or is otherwise involved in a specified event, activity, or operation.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aadb7bda1081908f2c41c520c9c55c |
completed | March 6, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61c0a0288190bce9d60062a84b69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.