Triple
T7812621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vesoul |
E180722
|
entity |
| Predicate | hasHistoricRegionRole |
P29914
|
FINISHED |
| Object | important town of Franche-Comté |
—
|
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: important town of Franche-Comté | Statement: [Vesoul, hasHistoricRegionRole, important town of Franche-Comté]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricRegionRole Context triple: [Vesoul, hasHistoricRegionRole, important town of Franche-Comté]
-
A.
hasHistoricalRoleAs
chosen
Indicates that an entity has served in a specific historical capacity, function, or position during a particular period or context.
-
B.
isInHistoricRegion
Indicates that an entity is located within or belongs to a historically recognized geographic region.
-
C.
historicalRegionCorrespondsTo
Indicates that a historical region matches or aligns with a specific region, territory, or administrative unit in terms of location, extent, or identity.
-
D.
historicalRegionAssociation
Indicates an association where an entity is or was located in, part of, or otherwise related to a specific historical region.
-
E.
historicalRegion
Indicates that an entity is or was a geographically defined area recognized for its significance during a particular historical period.
- 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_69ca827f6f148190beca4e245b993506 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78e198c81909d4fd227f6b71082 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae91687788190af9cb7aaa996d291 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:38 p.m.