Triple
T3849755
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yangtze river dolphin |
E85260
|
entity |
| Predicate | snoutCharacteristic |
P31173
|
FINISHED |
| Object | long narrow beak |
—
|
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: long narrow beak | Statement: [Yangtze river dolphin, snoutCharacteristic, long narrow beak]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: snoutCharacteristic Context triple: [Yangtze river dolphin, snoutCharacteristic, long narrow beak]
-
A.
noseType
Indicates the specific shape or classification of a nose that an entity possesses.
-
B.
hasColorOfNose
Indicates that one entity possesses a nose whose color matches or is characterized by the specified color entity.
-
C.
noseGearFeature
Indicates that there is a specific characteristic, component, or design attribute associated with the nose landing gear of an aircraft.
-
D.
hasBeak
Indicates that an entity possesses a beak as a physical anatomical feature.
-
E.
hasPhysicalFeature
chosen
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcde86081908cf3840ae002acfa |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:19 p.m.