Triple
T8720080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TER Bourgogne-Franche-Comté |
E206988
|
entity |
| Predicate | operatesInPartOfCountry |
P6665
|
FINISHED |
| Object | eastern France |
—
|
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: eastern France | Statement: [TER Bourgogne-Franche-Comté, operatesInPartOfCountry, eastern France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatesInPartOfCountry Context triple: [TER Bourgogne-Franche-Comté, operatesInPartOfCountry, eastern France]
-
A.
operatesInCountries
Indicates that an entity conducts its activities or business within the specified countries.
-
B.
operatedInRegion
chosen
Indicates that an entity conducted operations or activities within a specified geographic region.
-
C.
operatesBrandInRegion
Indicates that an entity manages or runs a specific brand within a particular geographic region.
-
D.
operatesToRegion
Indicates that an agent conducts operations or provides services directed toward or within a specified region.
-
E.
alsoInCountry
Indicates that something located in one country is additionally located or present in another specified country.
- 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_69ca835811d8819081ea00fd2a2c9a1c |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d02a52c81909f93622ae6920b80 |
completed | March 31, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_69cc457093188190959287a6458651c6 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:36 p.m.