Triple
T17565440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelwyn people |
E427799
|
entity |
| Predicate | definingPhysicalCharacteristic |
P56672
|
FINISHED |
| Object | short stature |
—
|
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 stature | Statement: [Nelwyn people, definingPhysicalCharacteristic, short stature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definingPhysicalCharacteristic Context triple: [Nelwyn people, definingPhysicalCharacteristic, short stature]
-
A.
dataCharacteristic
Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
-
B.
describesCharacteristicOf
chosen
Indicates that one entity expresses or specifies a characteristic, feature, or property of another entity.
-
C.
biologicalCharacteristic
Indicates that one entity possesses or exhibits a particular biological trait, feature, or property in relation to another.
-
D.
spanCharacteristic
Indicates that one entity has a particular measurable or descriptive property that characterizes the extent, duration, or range of another entity or phenomenon.
-
E.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4592ce42c8190a54a0a328c5e8ffc |
completed | April 19, 2026, 4:25 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.