Triple
T25833350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wat Plai Laem |
E650723
|
entity |
| Predicate | hasReligiousFigureDepicted |
P57866
|
FINISHED |
| Object | Guanyin |
—
|
NE NERFINISHED |
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: Guanyin | Statement: [Wat Plai Laem, hasReligiousFigureDepicted, Guanyin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasReligiousFigureDepicted Context triple: [Wat Plai Laem, hasReligiousFigureDepicted, Guanyin]
-
A.
mainReligionDepicted
Indicates that the primary religion represented or portrayed in a work, object, or context is the one specified.
-
B.
depictsReligiousDenomination
Indicates that one entity visually represents or portrays the religious denomination associated with another entity.
-
C.
hasReligiousFigureAssociation
chosen
Indicates a relationship in which an entity is connected or linked to a religious figure, such as through dedication, representation, influence, or affiliation.
-
D.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
-
E.
hasAllegoricalDepictionsBy
Indicates that one entity is represented through allegorical depictions created 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_69e7ab37438081908f1ccf6284839520 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: April 22, 2026, 7:39 a.m.