Triple
T31025129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Detachment 1, 9th Strategic Reconnaissance Wing |
E790547
|
entity |
| Predicate | operatedAircraftNickname |
P200545
|
FINISHED |
| Object | Habu |
—
|
NE NERFINISHED |
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: Habu | Statement: [Detachment 1, 9th Strategic Reconnaissance Wing, operatedAircraftNickname, Habu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatedAircraftNickname Context triple: [Detachment 1, 9th Strategic Reconnaissance Wing, operatedAircraftNickname, Habu]
-
A.
aircraftNicknamedFor
Indicates that an aircraft is commonly known or referred to by a particular nickname derived from or inspired by something else.
-
B.
notableAircraftCallsign
Indicates that a particular aircraft is notably associated with, or commonly identified by, a specific callsign.
-
C.
aircraftNamedIs
Indicates that a specific aircraft has the given name or designation.
-
D.
aircraftNicknameOrigin
Indicates the source or reason from which an aircraft’s nickname is derived.
-
E.
aircraftTypesOperated
Indicates the types or models of aircraft that an entity (such as an airline or operator) uses or operates.
- 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_69f224c811508190a7de096a5b1f5798 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff956dc6548190979171d4b4068d47 |
completed | May 9, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69ff93dc39c481908a97a12c3ef7dfe7 |
completed | May 9, 2026, 8:06 p.m. |
| PDg | Predicate description generation | batch_69ff956cd640819081efc31f313690b0 |
completed | May 9, 2026, 8:13 p.m. |
Created at: April 29, 2026, 8:58 p.m.