Triple
T27926857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint John the Baptist (El Greco) |
E707858
|
entity |
| Predicate | figureCharacteristic |
P128001
|
FINISHED |
| Object | slender proportions |
—
|
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: slender proportions | Statement: [Saint John the Baptist (El Greco), figureCharacteristic, slender proportions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: figureCharacteristic Context triple: [Saint John the Baptist (El Greco), figureCharacteristic, slender proportions]
-
A.
dataCharacteristic
Indicates that one entity specifies a property, attribute, or feature that characterizes a given piece of data.
-
B.
entityCharacteristic
chosen
Indicates that an entity possesses, exhibits, or is defined by a particular characteristic or attribute.
-
C.
catalogCharacteristic
Indicates that a catalog has a specific characteristic or attribute associated with it.
-
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.
featuresFigureOf
Indicates that one entity includes or presents another entity as a figure, illustration, or visual element.
- 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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f63fd6c68481908c542aa03e297b9c |
completed | May 2, 2026, 6:17 p.m. |
| PD | Predicate disambiguation | batch_69f63c6895f0819088655277e45859a8 |
completed | May 2, 2026, 6:03 p.m. |
Created at: April 27, 2026, 7 p.m.