Triple
T9954711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | javelina |
E195416
|
entity |
| Predicate | hasToesPerFoot |
P32339
|
FINISHED |
| Object | three functional toes on each hind foot |
—
|
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: three functional toes on each hind foot | Statement: [javelina, hasToesPerFoot, three functional toes on each hind foot]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasToesPerFoot Context triple: [javelina, hasToesPerFoot, three functional toes on each hind foot]
-
A.
hasToeCount
chosen
Indicates that an entity possesses a specified number of toes.
-
B.
hasStandardToeCount
Indicates that an entity possesses the typical or expected number of toes for its kind.
-
C.
toeShape
Indicates the specific form or contour of an entity’s toe or toe area.
-
D.
zygodactylFeetDescription
Indicates that an entity possesses zygodactyl feet, meaning its toes are arranged in two opposing pairs (typically two forward and two backward).
-
E.
footType
Indicates the specific kind or classification of feet that an entity possesses or is characterized by.
- 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_69ca82eaaa008190a54fa1a9f954b9ad |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdb694b95481909d049302818e7137 |
completed | April 2, 2026, 12:21 a.m. |
| PD | Predicate disambiguation | batch_69cd1d97c44081908730071269f07712 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:46 p.m.