Triple
T6011840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hunchback |
E133852
|
entity |
| Predicate | aircraftNicknameOrigin |
P68741
|
FINISHED |
| Object | derived from humped fuselage shape |
—
|
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: derived from humped fuselage shape | Statement: [Hunchback, aircraftNicknameOrigin, derived from humped fuselage shape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftNicknameOrigin Context triple: [Hunchback, aircraftNicknameOrigin, derived from humped fuselage shape]
-
A.
notableAircraftCallsign
Indicates that a particular aircraft is notably associated with, or commonly identified by, a specific callsign.
-
B.
referredAircraftCommonName
Indicates that one entity mentions or identifies an aircraft using its commonly known name.
-
C.
aircraftNamedAfterSpouse
Indicates that an aircraft is named in honor of the spouse of a particular person.
-
D.
originalJetsName
Indicates that one entity is the original or former name of the Jets team associated with the other entity.
-
E.
firstAircraftName
Indicates the name assigned to the first aircraft associated with a given entity or context.
- 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_69c0087361a48190905c6b55969852b8 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f5159bc8190a988293bbbb99d24 |
completed | March 22, 2026, 8:21 p.m. |
| PD | Predicate disambiguation | batch_69c049e4daf4819099bf870dc700e0a2 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:06 p.m.