Triple
T2427682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gritty |
E53568
|
entity |
| Predicate | appearanceFeature |
P25983
|
FINISHED |
| Object | large round nose |
—
|
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: large round nose | Statement: [Gritty, appearanceFeature, large round nose]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appearanceFeature Context triple: [Gritty, appearanceFeature, large round nose]
-
A.
appearance
Indicates how something looks or seems to an observer, including its visible form, condition, or outward impression.
-
B.
hasPhysicalFeature
Indicates that one entity possesses or exhibits a specific physical characteristic or feature of another entity.
-
C.
visualFeature
chosen
Indicates a relationship where one entity possesses or exhibits a particular visual characteristic or attribute of another entity.
-
D.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
E.
adaptationAppearance
Indicates that one entity appears or is depicted in an adaptation of another entity (such as a work being represented in a derived or reinterpreted version).
- 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_69ab495c44d48190b7235b23719bc3f6 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcc74a5108190a3a9631b0cc1a127 |
completed | March 7, 2026, 6:57 a.m. |
| PD | Predicate disambiguation | batch_69abc5aa1b60819081b87f7985c6cff3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:42 p.m.