Triple
T33571841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Japanese serow |
E859920
|
entity |
| Predicate | hornDescription |
P167512
|
FINISHED |
| Object | short backward-curving horns in both sexes |
—
|
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: short backward-curving horns in both sexes | Statement: [Japanese serow, hornDescription, short backward-curving horns in both sexes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hornDescription Context triple: [Japanese serow, hornDescription, short backward-curving horns in both sexes]
-
A.
hornPattern
chosen
Indicates the specific arrangement, shape, or configuration of an entity’s horn or horns in relation to its head or body.
-
B.
hornSheath
Indicates that one entity is the protective outer covering or sheath surrounding the horn of another entity.
-
C.
hornConfiguration
Indicates how the horns of an entity are arranged, shaped, or configured in relation to each other.
-
D.
hornInterpretedAs
Indicates that one entity’s horn is understood, interpreted, or taken to represent another entity or concept.
-
E.
hornPosition
Indicates the relative placement or orientation of a horn with respect to a reference point or object.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f74620dc819081b0aeb6490815eb |
completed | May 3, 2026, 7:20 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:40 a.m.