Triple
T26706523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chauna chavaria |
E673299
|
entity |
| Predicate | hasAirSacs |
P161146
|
FINISHED |
| Object | enlarged subcutaneous air sacs |
—
|
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: enlarged subcutaneous air sacs | Statement: [Chauna chavaria, hasAirSacs, enlarged subcutaneous air sacs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAirSacs Context triple: [Chauna chavaria, hasAirSacs, enlarged subcutaneous air sacs]
-
A.
hasAirConditioning
Indicates that an entity is equipped with or provides air conditioning.
-
B.
hasAirComponent
Indicates that something includes, contains, or is associated with an air-related component or element.
-
C.
hasEjectionSeat
Indicates that an object (typically a vehicle or cockpit) is equipped with an ejection seat that allows an occupant to be forcibly expelled for emergency escape.
-
D.
hasPassengerInformationSystem
Indicates that an entity is equipped with a system that provides information to passengers, such as schedules, announcements, or travel updates.
-
E.
hasBaggageSystem
Indicates that an entity is equipped with or utilizes a baggage handling system.
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f617b9d9648190a1f50ece0815b857 |
completed | May 2, 2026, 3:26 p.m. |
| PD | Predicate disambiguation | batch_69f60b8dfa0c8190864e1a940024d0a0 |
completed | May 2, 2026, 2:34 p.m. |
| PDg | Predicate description generation | batch_69f6106d346c8190868489f36c65b6ec |
completed | May 2, 2026, 2:55 p.m. |
Created at: April 27, 2026, 3:34 a.m.