Triple
T13505044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tk (macrolanguage) |
E320993
|
entity |
| Predicate | hasISO639-2BibliographicCode |
P5197
|
FINISHED |
| Object | tuk |
—
|
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: tuk | Statement: [tk (macrolanguage), hasISO639-2BibliographicCode, tuk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasISO639-2BibliographicCode Context triple: [tk (macrolanguage), hasISO639-2BibliographicCode, tuk]
-
A.
languageCodeISO639-2
chosen
Indicates that an entity is associated with a language identified by its ISO 639-2 three-letter code.
-
B.
ISO639-2Equivalent
Indicates that two language identifiers are equivalent according to the ISO 639-2 language code standard.
-
C.
ISO639-1Equivalent
Indicates that two language identifiers are equivalent according to the ISO 639-1 two-letter language code standard.
-
D.
ISO639CollectiveCode
Indicates that the relationship assigns or associates an ISO 639 collective language code (a code representing a group of related languages) to the relevant language entity or set of languages.
-
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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf810e248190a060481004503f96 |
completed | April 12, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69dbae0b63748190b5e207f84b2532ea |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:43 p.m.