Triple
T25133683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FR-42 |
E629596
|
entity |
| Predicate | hasLanguageNeutralFormat |
P7055
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [FR-42, hasLanguageNeutralFormat, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageNeutralFormat Context triple: [FR-42, hasLanguageNeutralFormat, true]
-
A.
hasLanguageCodeFormat
Indicates that there is a specified structural or syntactic format that language codes associated with an entity must follow.
-
B.
isLanguageIndependent
Indicates that the relationship, property, or behavior holds true regardless of the specific natural language used to express or encode it.
-
C.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal language.
-
D.
languageNeutral
chosen
Indicates that the relationship or action is independent of any specific natural language, applying uniformly across different linguistic contexts.
-
E.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
- 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_69e2ff338250819096ff6c8892804389 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f66c5c13808190887180099745673b |
completed | May 2, 2026, 9:27 p.m. |
| PD | Predicate disambiguation | batch_69f66abddc448190a488852f8abdeb2c |
completed | May 2, 2026, 9:21 p.m. |
Created at: April 18, 2026, 6:28 a.m.