Triple
T26667535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Antigone district |
E672226
|
entity |
| Predicate | languageUsedForToponyms |
P24399
|
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: [Antigone district, languageUsedForToponyms, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedForToponyms Context triple: [Antigone district, languageUsedForToponyms, French]
-
A.
hasLanguageOfToponym
chosen
Indicates that a place name (toponym) is expressed in or associated with a particular language.
-
B.
influenceOnToponymy
Indicates that one entity has affected or shaped the naming, form, or development of place names associated with another entity.
-
C.
toponymsShareSpelling
Indicates that two place names share the same or very similar written form or spelling.
-
D.
hasEthnolinguisticOriginOfToponym
Indicates that a toponym (place name) originates from or is derived from a particular ethnolinguistic group or language.
-
E.
toponymLiteralMeaning
Indicates the literal or etymological meaning of a place name (toponym), describing what the name directly translates to or signifies.
- 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_69eecda00a9c8190b2691f4d89db03b6 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fbad1e94988190b86d447a68e65067 |
completed | May 6, 2026, 9:05 p.m. |
| PD | Predicate disambiguation | batch_69fba881b8e0819094790935152b99a1 |
completed | May 6, 2026, 8:45 p.m. |
Created at: April 27, 2026, 3:11 a.m.