Triple
T7002373
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King of Siam |
E162365
|
entity |
| Predicate | modernEquivalentTitle |
P21626
|
FINISHED |
| Object | King of Thailand |
—
|
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: King of Thailand | Statement: [King of Siam, modernEquivalentTitle, King of Thailand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernEquivalentTitle Context triple: [King of Siam, modernEquivalentTitle, King of Thailand]
-
A.
modernEquivalent
chosen
Indicates that one entity serves as the contemporary or updated counterpart of another earlier or traditional entity.
-
B.
modernEditionBy
Indicates that one entity is a modern edition or updated version that has been prepared, edited, or published by another entity.
-
C.
analogousTitle
Indicates that one entity has a title or position that corresponds in role, rank, or function to the title or position held by another entity.
-
D.
equivalentOrRelatedTitle
Indicates that two titles are the same or sufficiently similar in meaning, role, or status to be treated as equivalent or closely related.
-
E.
equivalentTitleInFrench
Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
- 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.