Triple
T5701157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gréville-Hague |
E125664
|
entity |
| Predicate | hasNativeLanguage |
P151
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Gréville-Hague, hasNativeLanguage, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNativeLanguage Context triple: [Gréville-Hague, hasNativeLanguage, French]
-
A.
hasNativeSpeakers
Indicates that a language or dialect is spoken as a first language by one or more people or populations.
-
B.
nativeLanguage
chosen
Indicates the language that a person or entity originally learned and uses as their primary or first language.
-
C.
hasRepresentativeLanguage
Indicates that an entity is associated with a language that serves as its primary or officially recognized means of representation or communication.
-
D.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
-
E.
isLinguaFrancaOf
Indicates that a language serves as a common medium of communication between speakers of different native languages within a particular region, community, or context.
- 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_69c0082c96988190b3a6a201edce472a |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024540afc8190aee3760f71ea39c2 |
completed | March 22, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69c021c2d8bc8190b947c7d1f423d2f3 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:45 p.m.