Triple
T34187642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thanboddhay Pagoda |
E877004
|
entity |
| Predicate | hasTypeOfImage |
P56789
|
FINISHED |
| Object | seated Buddha statues |
—
|
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: seated Buddha statues | Statement: [Thanboddhay Pagoda, hasTypeOfImage, seated Buddha statues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfImage Context triple: [Thanboddhay Pagoda, hasTypeOfImage, seated Buddha statues]
-
A.
hasImageType
chosen
Indicates that an entity is associated with an image of a particular type or format.
-
B.
hasImagingType
Indicates the specific imaging modality or technique associated with or used in a given imaging procedure or result.
-
C.
isImageOf
Indicates that one entity is a visual depiction or representation of another entity.
-
D.
hasImageFeature
Indicates that an entity is associated with a specific visual characteristic or attribute extracted from an image.
-
E.
hasImageryType
Indicates that one entity is associated with a specific kind or category of imagery (such as visual style, medium, or representation type) used to depict or describe it.
- 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_69f349ae640c8190b9cd220b5368d8b6 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff255b84788190a94682f4efe1d0b8 |
completed | May 9, 2026, 12:15 p.m. |
| PD | Predicate disambiguation | batch_69ff24f3ab108190bb017a656cff3d82 |
completed | May 9, 2026, 12:13 p.m. |
Created at: May 1, 2026, 1:55 a.m.