Triple
T7002376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of Siam |
E162365
|
entity |
| Predicate | associatedReligionTitle |
P13363
|
FINISHED |
| Object | Upholder of the Buddhist Faith |
—
|
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: Upholder of the Buddhist Faith | Statement: [King of Siam, associatedReligionTitle, Upholder of the Buddhist Faith]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedReligionTitle Context triple: [King of Siam, associatedReligionTitle, Upholder of the Buddhist Faith]
-
A.
associatedReligionText
Indicates that there is a textual work (such as a scripture or religious document) that is specifically associated with, or pertains to, a given religion.
-
B.
associatedReligionRole
Indicates that one entity holds a specific religious role, office, or function in relation to another entity.
-
C.
titleHolderReligion
Indicates the religious affiliation associated with the holder of a particular title.
-
D.
associatedReligionInTexts
Indicates that a particular religion is mentioned or linked in written texts in connection with the given entity.
-
E.
religiousName
chosen
Indicates that an entity has or is known by a name specifically associated with a religious role, identity, or context.
- 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_69c68857ffc08190857dc62cd5253777 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc1115c48190a9363473ae21b6c1 |
completed | March 27, 2026, 7:35 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c67c94819084fdcf0398606027 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:33 p.m.