Triple
T24757479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yabem–Takia language continuum |
E619330
|
entity |
| Predicate | hasCoreLanguages |
P161420
|
FINISHED |
| Object | Yabem |
—
|
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: Yabem | Statement: [Yabem–Takia language continuum, hasCoreLanguages, Yabem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoreLanguages Context triple: [Yabem–Takia language continuum, hasCoreLanguages, Yabem]
-
A.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
B.
hasLanguageResources
Indicates that an entity possesses or provides resources related to a particular language, such as tools, materials, or services supporting its use or study.
-
C.
hasApproximateNumberOfLanguages
Indicates that an entity is associated with a quantity representing an estimated or non-exact count of languages.
-
D.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
hasMajorityLanguageServices
Indicates that one language is used for the majority of services or service interactions within a given context or system.
- F. None of above. chosen
Provenance (4 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_69e2fabbea94819092ed41348909622f |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f613bc641c819084343cc78d080640 |
completed | May 2, 2026, 3:09 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
| PDg | Predicate description generation | batch_69f613502d808190b89927e5e734b43a |
completed | May 2, 2026, 3:08 p.m. |
Created at: April 18, 2026, 4:26 a.m.