Triple
T24861328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pattani railway station |
E622159
|
entity |
| Predicate | languageOfStationCode |
P128274
|
FINISHED |
| Object | Thai |
—
|
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: Thai | Statement: [Pattani railway station, languageOfStationCode, Thai]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfStationCode Context triple: [Pattani railway station, languageOfStationCode, Thai]
-
A.
hasLanguageVariantsAtStation
Indicates that a station supports multiple language variants for its information, services, or interfaces.
-
B.
codeForStationIn
Indicates that a specific code is assigned to or used to identify a station within a particular system, network, or context.
-
C.
languageCodeISO639-2
Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
-
D.
languageOfCodes
chosen
Indicates that a particular language is used for or associated with a given set of codes.
-
E.
languageCodeISO639-1
Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
- 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_69e2fac350d08190b3affde1b451a8c5 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f650c70d7c819093d9a0f005f7c8d5 |
completed | May 2, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69f64cab1f648190a2a9460690d18a37 |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 18, 2026, 5:22 a.m.