Triple
T34818641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | เขตดอนเมือง |
E1003705
|
entity |
| Predicate | hasFormerEnglishName |
P139362
|
FINISHED |
| Object | Don Muang District |
—
|
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: Don Muang District | Statement: [เขตดอนเมือง, hasFormerEnglishName, Don Muang District]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerEnglishName Context triple: [เขตดอนเมือง, hasFormerEnglishName, Don Muang District]
-
A.
hasLaterNameInEnglish
Indicates that an entity is known by a different English name at a later time or in a subsequent context.
-
B.
historicalNameInEnglish
chosen
Indicates that an entity is associated with a historical English-language name by which it was known in the past.
-
C.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
D.
hasEnglishNameVariant
Indicates that one entity is an alternative or variant form of another entity’s name specifically in the English language.
-
E.
languageOfHistoricName
Indicates the language in which a historic or former name of an entity is expressed.
- 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_69f76db717088190811b4e744610f37d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fe12a899d4819080d48423f32eace9 |
completed | May 8, 2026, 4:43 p.m. |
| PD | Predicate disambiguation | batch_69fe0d7f6aa08190a1d2dfc025d4e0dc |
completed | May 8, 2026, 4:21 p.m. |
Created at: May 3, 2026, 4 p.m.