Triple
T2245529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ERC Advanced Grant |
E49492
|
entity |
| Predicate | applicationLanguage |
P18209
|
FINISHED |
| Object | English |
—
|
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: English | Statement: [ERC Advanced Grant, applicationLanguage, English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: applicationLanguage Context triple: [ERC Advanced Grant, applicationLanguage, English]
-
A.
languageUse
chosen
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
B.
languageOfEnvironment
Indicates the language predominantly used or present in a given environment or context.
-
C.
languageProvision
Indicates that one entity supplies, supports, or makes available a particular language (or set of languages) for use by another entity.
-
D.
languageVariant
Indicates that one language is a variant, dialect, or localized form of another language.
-
E.
regionLanguage
Indicates that a particular language is used or officially recognized within a specific geographic 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ea75d881909d4e176a432f32e8 |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.