Triple
T29759454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CLIL |
E753719
|
entity |
| Predicate | typicalTargetLanguage |
P42338
|
FINISHED |
| Object | English |
E211
|
NE 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: English | Statement: [CLIL, typicalTargetLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTargetLanguage Context triple: [CLIL, typicalTargetLanguage, English]
-
A.
targetLanguage
Indicates the language that is the intended recipient or focus of a communication, translation, or linguistic operation.
-
B.
targetsLanguage
Indicates that an action, resource, or entity is specifically directed toward, designed for, or intended to be used with a particular language.
-
C.
languageTargets
Indicates that a language is specifically directed at, intended for, or used to address a particular target entity (such as an audience, system, or domain).
-
D.
typicalLanguages
chosen
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
-
E.
translationTargetLanguage
Indicates the language into which content is being or has been translated.
- F. None of above.
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_69f0ef827ff88190ade56e0b0846b713 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a02f2d6f35481909829d4ec710dcb0f |
completed | May 12, 2026, 9:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a26c8ed270481909286517987e89711 |
completed | June 8, 2026, 1:51 p.m. |
| PD | Predicate disambiguation | batch_6a02f15a2460819080cb4be5b50221d0 |
completed | May 12, 2026, 9:22 a.m. |
Created at: April 28, 2026, 8:31 p.m.