Triple
T13431701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | pos (Sayula Popoluca) |
E313626
|
entity |
| Predicate | ISO 639-3 code |
P8719
|
FINISHED |
| Object | pos |
—
|
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: pos | Statement: [pos (Sayula Popoluca), ISO 639-3 code, pos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ISO 639-3 code Context triple: [pos (Sayula Popoluca), ISO 639-3 code, pos]
-
A.
ISO639-3CodeOfLanguage
Indicates that one entity is the ISO 639-3 three-letter language code assigned to the language represented by the other entity.
-
B.
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.
-
C.
ISO639-6Code
Indicates the standardized ISO 639-6 four-letter code that uniquely identifies a specific language variety or dialect.
-
D.
hasISO6393Code
chosen
Indicates that a language or linguistic entity is associated with a specific ISO 639-3 three-letter language code.
-
E.
ISO639-2Equivalent
Indicates that two language identifiers are equivalent according to the ISO 639-2 language code standard.
- 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_69d806ad0c44819088833ae1ec9e9690 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaed41a5481908800033303224adb |
completed | April 12, 2026, 2:40 p.m. |
| PD | Predicate disambiguation | batch_69d9a03926188190ab3948d1f5d3941f |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:40 p.m.