Triple
T24119381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yangochiroptera |
E597607
|
entity |
| Predicate | hasBodySizeRange |
P31708
|
FINISHED |
| Object | small to medium-sized mammals |
—
|
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: small to medium-sized mammals | Statement: [Yangochiroptera, hasBodySizeRange, small to medium-sized mammals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodySizeRange Context triple: [Yangochiroptera, hasBodySizeRange, small to medium-sized mammals]
-
A.
hasBodyLengthRange
chosen
Indicates the range of possible body lengths associated with an entity, typically expressed as a minimum and maximum value.
-
B.
memberOfBodySize
Indicates that one entity is a component or part whose size contributes to or characterizes the overall body size of another entity.
-
C.
hasLengthRange
Indicates that an entity’s length falls within a specified minimum-to-maximum range.
-
D.
hasBodyOf
Indicates that one entity possesses, contains, or is composed of the physical body or main substance of another entity.
-
E.
includesSizeRange
Indicates that one entity specifies or covers a particular range of sizes associated with 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_69e288c74200819098ab875b592cb39f |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1dee1a2608190870ade02495c5ebe |
completed | April 29, 2026, 10:35 a.m. |
| PD | Predicate disambiguation | batch_69f1765650fc8190a6bc1eb512b240bf |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:05 p.m.