Triple
T14386230
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cham language |
E356729
|
entity |
| Predicate | iso6391Code |
P5196
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Cham language, iso6391Code, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: iso6391Code Context triple: [Cham language, iso6391Code, none]
-
A.
ISO639-1CodeFor
Indicates that one entity is the ISO 639-1 two-letter language code corresponding to the language represented by the other entity.
-
B.
languageCodeISO639-2
Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
-
C.
languageCodeISO639-1
chosen
Indicates that the subject entity is associated with the specified two-letter ISO 639-1 language code.
-
D.
ISO639-6Code
Indicates the standardized ISO 639-6 four-letter code that uniquely identifies a specific language variety or dialect.
-
E.
sharesISO639-3CodeWith
Indicates that two language entities share the same ISO 639-3 code, meaning they are treated as the same language in that coding system.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de9025cff881908c08224d90d9f750 |
completed | April 14, 2026, 7:06 p.m. |
| PD | Predicate disambiguation | batch_69de2aa024c48190805df6a9d63deb10 |
completed | April 14, 2026, 11:53 a.m. |
Created at: April 10, 2026, 1:16 a.m.