Triple
T16351354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakh languages |
E397067
|
entity |
| Predicate | numberOfMajorLanguages |
P123074
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Nakh languages, numberOfMajorLanguages, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMajorLanguages Context triple: [Nakh languages, numberOfMajorLanguages, 3]
-
A.
estimatedNumberOfLanguages
Indicates the approximate count of distinct languages associated with an entity, typically based on estimation rather than an exact measurement.
-
B.
hasApproximateNumberOfLanguages
Indicates that an entity is associated with a quantity representing an estimated or non-exact count of languages.
-
C.
shareMajorLanguage
Indicates that the entities have at least one primary or major language in common.
-
D.
currentNumberOfLanguages
Indicates the present count of distinct languages associated with or used by a given entity.
-
E.
numberOfScheduledLanguages
Indicates the total count of distinct languages that have been formally scheduled or planned for use in 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_69d87f26864c819088365ca381a003c2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2facb37d0819093fe45446f1e79c1 |
completed | April 18, 2026, 3:30 a.m. |
| PD | Predicate disambiguation | batch_69e226f37ecc819082af58b29b4e39d1 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:07 a.m.