Triple
T18204839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XLM-R |
E435876
|
entity |
| Predicate | supportsLanguagesCountApprox |
P14732
|
FINISHED |
| Object | 100+ |
—
|
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: 100+ | Statement: [XLM-R, supportsLanguagesCountApprox, 100+]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsLanguagesCountApprox Context triple: [XLM-R, supportsLanguagesCountApprox, 100+]
-
A.
hasApproximateNumberOfLanguages
Indicates that an entity is associated with a quantity representing an estimated or non-exact count of languages.
-
B.
estimatedNumberOfLanguages
chosen
Indicates the approximate count of distinct languages associated with an entity, typically based on estimation rather than an exact measurement.
-
C.
currentNumberOfLanguages
Indicates the present count of distinct languages associated with or used by a given entity.
-
D.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
E.
numberOfMajorLanguages
Indicates the total count of major languages associated with a given 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e222831081908f7d5500424e3acb |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:32 a.m.