Triple
T22296646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jarawan languages |
E551137
|
entity |
| Predicate | haveNumberOfLanguages |
P13692
|
FINISHED |
| Object | around 20 varieties |
—
|
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: around 20 varieties | Statement: [Jarawan languages, haveNumberOfLanguages, around 20 varieties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveNumberOfLanguages Context triple: [Jarawan languages, haveNumberOfLanguages, around 20 varieties]
-
A.
hasApproximateNumberOfLanguages
chosen
Indicates that an entity is associated with a quantity representing an estimated or non-exact count of languages.
-
B.
estimatedNumberOfLanguages
Indicates the approximate count of distinct languages associated with an entity, typically based on estimation rather than an exact measurement.
-
C.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
D.
currentNumberOfLanguages
Indicates the present count of distinct languages associated with or used by a given entity.
-
E.
originalNumberOfLanguages
Indicates the initial count of distinct languages associated with an entity before any changes or reductions occur.
- 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15720fba0819080f6c96f6df4f1e0 |
completed | April 29, 2026, 12:56 a.m. |
| PD | Predicate disambiguation | batch_69e72ffa438481908f80879aef2a589b |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:41 p.m.