Triple
T26070422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utupua |
E657526
|
entity |
| Predicate | hasMainLanguageFamily |
P109306
|
FINISHED |
| Object | Austronesian languages |
—
|
NE NERFINISHED |
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: Austronesian languages | Statement: [Utupua, hasMainLanguageFamily, Austronesian languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainLanguageFamily Context triple: [Utupua, hasMainLanguageFamily, Austronesian languages]
-
A.
hasPrimaryVernacularLanguageFamily
chosen
Indicates that an entity’s main vernacular language belongs to a specified language family.
-
B.
includesMajorLanguageFamily
Indicates that one entity encompasses, contains, or is associated with a major language family as part of its scope or classification.
-
C.
isInLanguageFamily
Indicates that a language belongs to, or is classified within, a particular language family based on shared linguistic ancestry or characteristics.
-
D.
usesLanguageFamily
Indicates that an entity communicates or operates using a language that belongs to a specified language family.
-
E.
hasSecondaryLanguageFamily
Indicates that an entity has an additional, non-primary association with a particular language family.
- 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_69ee5bbe539081909efc7f9dd7c1b53c |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
Created at: April 26, 2026, 7:28 p.m.