Triple
T35902678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wat Si Chum |
E1038393
|
entity |
| Predicate | buddhaImageMaterial |
P127906
|
FINISHED |
| Object | stucco over brick |
—
|
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: stucco over brick | Statement: [Wat Si Chum, buddhaImageMaterial, stucco over brick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buddhaImageMaterial Context triple: [Wat Si Chum, buddhaImageMaterial, stucco over brick]
-
A.
imageMaterial
chosen
Indicates that one entity serves as the material or physical medium from which the image entity is composed or rendered.
-
B.
templeMaterial
Indicates that a temple is constructed from, or primarily composed of, a specified material.
-
C.
stringMaterialDepicted
Indicates that one entity is a string material that is visually represented or depicted by another entity.
-
D.
materialDepicted
Indicates that a work or representation visually portrays or includes a particular material as part of its subject.
-
E.
exampleMaterial
Indicates that something serves as a representative or illustrative material or sample of something else.
- 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_69f76e2190f88190beb2eed798a4ef01 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7b5ccbda481908fe1945c35e36ce8 |
completed | May 3, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c06f5881908f0b98cad6796478 |
completed | May 3, 2026, 8:49 p.m. |
Created at: May 3, 2026, 4:07 p.m.