Triple
T4211662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinthe |
E93915
|
entity |
| Predicate | isTypicallyDepictedAs |
P18297
|
FINISHED |
| Object | lion-like creature |
—
|
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: lion-like creature | Statement: [Chinthe, isTypicallyDepictedAs, lion-like creature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isTypicallyDepictedAs Context triple: [Chinthe, isTypicallyDepictedAs, lion-like creature]
-
A.
oftenDepictedAs
chosen
Indicates that one entity is frequently represented or portrayed in the form, appearance, or symbolism of another entity.
-
B.
depictionType
Indicates the specific manner or style in which something is visually represented or depicted.
-
C.
commonlyDepictedOn
Indicates that something is frequently shown or represented on the surface, medium, or context of another thing.
-
D.
typicalFigure
Indicates that one entity serves as a standard or representative example (a typical instance) of the other entity.
-
E.
depictsCharacterType
Indicates that one entity visually represents or portrays a character of a specified type or role.
- 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_69b3451743608190808f41d17ccf2650 |
completed | March 12, 2026, 10:58 p.m. |
| NER | Named-entity recognition | batch_69b34e098da881909a0cc339cc186627 |
completed | March 12, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69b347efd9b08190bb50f82e4e7fe06d |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:04 p.m.