Triple
T36670185
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapirus |
E905389
|
entity |
| Predicate | hasSnoutFunction |
P87407
|
FINISHED |
| Object | grasping vegetation |
—
|
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: grasping vegetation | Statement: [Tapirus, hasSnoutFunction, grasping vegetation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSnoutFunction Context triple: [Tapirus, hasSnoutFunction, grasping vegetation]
-
A.
hasSnoutAdaptation
chosen
Indicates that an entity possesses a specific modification or specialized feature of its snout adapted for a particular function or environment.
-
B.
haveSnouts
Indicates that the subject possesses or is characterized by snouts.
-
C.
snoutType
Indicates the type or form of an entity’s snout in relation to its overall morphology.
-
D.
hasTypeOfMouth
Indicates that an entity possesses a mouth characterized by a specific type or form.
-
E.
hasTeethAdaptedFor
Indicates that an organism’s teeth are specially shaped or structured to suit a particular function, diet, or environmental condition.
- 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_69f76e6f10008190aea41746aa1b186e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c79dede081909607d64d3cd1aeb2 |
completed | May 3, 2026, 10:09 p.m. |
| PD | Predicate disambiguation | batch_69f7c4796ebc819084a0dc08505e5f14 |
completed | May 3, 2026, 9:56 p.m. |
Created at: May 3, 2026, 4:12 p.m.