Triple
T3475963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | proboscis monkey |
E73374
|
entity |
| Predicate | noseFunction |
P49196
|
FINISHED |
| Object | used in vocalization and sexual selection |
—
|
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: used in vocalization and sexual selection | Statement: [proboscis monkey, noseFunction, used in vocalization and sexual selection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noseFunction Context triple: [proboscis monkey, noseFunction, used in vocalization and sexual selection]
-
A.
noseType
Indicates the specific shape or classification of a nose that an entity possesses.
-
B.
noseGearFeature
Indicates that there is a specific characteristic, component, or design attribute associated with the nose landing gear of an aircraft.
-
C.
hasColorOfNose
Indicates that one entity possesses a nose whose color matches or is characterized by the specified color entity.
-
D.
noseGearOrigin
Indicates the point or location from which the nose landing gear of an aircraft extends or is mounted.
-
E.
notFunction
Indicates that the specified entity does not serve as a function or is not used in a functional role within the given 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_69ad85b2fed48190948c8765e453d270 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbb593a388190b7786190deba96ed |
completed | March 8, 2026, 6:09 p.m. |
| PD | Predicate disambiguation | batch_69adae07802c8190919c49b0e65b2797 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adb21a437c81908bca88d5e123d744 |
completed | March 8, 2026, 5:30 p.m. |
Created at: March 8, 2026, 3:17 p.m.