Triple
T17200561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boy with Thorn |
E417461
|
entity |
| Predicate | detailFeature |
P41649
|
FINISHED |
| Object | carefully rendered anatomy |
—
|
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: carefully rendered anatomy | Statement: [Boy with Thorn, detailFeature, carefully rendered anatomy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: detailFeature Context triple: [Boy with Thorn, detailFeature, carefully rendered anatomy]
-
A.
featureType
Indicates the specific kind or category of feature that characterizes or distinguishes an entity.
-
B.
featuresIn
Indicates that an entity appears or plays a role within another entity, such as a person or element being included in a work, event, or context.
-
C.
displaysFeature
chosen
Indicates that one entity presents, shows, or makes visible a particular feature or characteristic of another entity.
-
D.
specialFeature
Indicates that an entity possesses a distinctive or noteworthy attribute, capability, or characteristic that sets it apart from others.
-
E.
featuresDecor
Indicates that one entity includes or showcases the decor elements provided or defined by 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_69d886d6ba8c819093215917b3d01689 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42daf2e5c81909c97d2e7a3ed7b88 |
completed | April 19, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69e3831e354881908c5505ffd15c84e9 |
completed | April 18, 2026, 1:11 p.m. |
Created at: April 10, 2026, 5:38 a.m.