Triple
T32002957
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nyulnyul people |
E817182
|
entity |
| Predicate | haveDistinctLanguage |
P152149
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Nyulnyul people, haveDistinctLanguage, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveDistinctLanguage Context triple: [Nyulnyul people, haveDistinctLanguage, true]
-
A.
hasOwnLanguage
chosen
Indicates that an entity possesses or uses a distinct language of its own.
-
B.
recognizedAsDistinctLanguageFrom
Indicates that one language is formally acknowledged or treated as a separate and distinct language from another, rather than as a dialect or variant of it.
-
C.
haveDistinctOfficialLanguages
Indicates that the two entities each have their own official language and these official languages are not the same.
-
D.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
hasLinguisticVariety
Indicates that one entity possesses or exhibits a particular linguistic variety in relation to another entity or context.
- 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_69f348f8ce388190ae84376b1f348f12 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b3fdd830819089e39d9112ea771f |
completed | May 3, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:14 a.m.