Triple
T27316806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ardipithecus |
E689369
|
entity |
| Predicate | footMorphologyIndicates |
P161154
|
FINISHED |
| Object | grasping big toe and arboreal capabilities |
—
|
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 big toe and arboreal capabilities | Statement: [Ardipithecus, footMorphologyIndicates, grasping big toe and arboreal capabilities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: footMorphologyIndicates Context triple: [Ardipithecus, footMorphologyIndicates, grasping big toe and arboreal capabilities]
-
A.
footMorphologySuggests
chosen
Indicates that the structure or shape of a foot provides evidence or clues pointing toward a particular characteristic, behavior, or classification.
-
B.
footType
Indicates the specific kind or classification of feet that an entity possesses or is characterized by.
-
C.
toeShape
Indicates the specific form or contour of an entity’s toe or toe area.
-
D.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
E.
hasFootName
Indicates that an entity has a foot (or feet) identified by a specific name.
- 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_69ef355c53a08190a8a92e355a7ce115 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f627b69d0881908e5da0d2d6acedae |
completed | May 2, 2026, 4:35 p.m. |
| PD | Predicate disambiguation | batch_69f620e4b1c88190a17940251abc68fd |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 27, 2026, 11:31 a.m.