Triple
T25684725
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lhao Vo language |
E644034
|
entity |
| Predicate | hasVarieties |
P88640
|
FINISHED |
| Object | local village-based varieties (poorly documented) |
—
|
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: local village-based varieties (poorly documented) | Statement: [Lhao Vo language, hasVarieties, local village-based varieties (poorly documented)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVarieties Context triple: [Lhao Vo language, hasVarieties, local village-based varieties (poorly documented)]
-
A.
hasVarietyOf
chosen
Indicates that an entity possesses or offers multiple different types, forms, or versions of something.
-
B.
hasNonStandardizedVarieties
Indicates that an entity possesses forms or variants that are not governed by a uniform or officially established standard.
-
C.
hasApproximateNumberOfVarieties
Indicates that an entity is associated with an estimated or non-exact count of different varieties or types.
-
D.
has32Varieties
Indicates that one entity possesses or includes exactly 32 distinct types, forms, or varieties of another entity.
-
E.
hasHigherVariety
Indicates that one entity offers or contains a greater diversity or range of items, types, or options than another entity.
- 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_69e77e8046888190b07ffa58c7e2c37a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fb7c000c819094efdcbb23ebddae |
completed | May 2, 2026, 1:26 p.m. |
| PD | Predicate disambiguation | batch_69f4a0f7c6008190ae8cee3e71e19b94 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 21, 2026, 8:06 p.m.