Triple
T22637048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Chartres railway line |
E558708
|
entity |
| Predicate | terminus |
P388
|
FINISHED |
| Object | Chartres |
—
|
NE NERFINISHED |
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: Chartres | Statement: [Paris–Chartres railway line, terminus, Chartres]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chartres Context triple: [Paris–Chartres railway line, terminus, Chartres]
-
A.
Chartres
chosen
Chartres is a historic city in northern France renowned for its well-preserved medieval old town and its UNESCO-listed Gothic cathedral, famed for its stained glass windows.
-
B.
Chartres
Chartres is a small rural settlement located on West Falkland in the Falkland Islands.
-
C.
Cholet
Cholet is a town in western France’s Maine-et-Loire department, known historically for its textile industry and as part of the Pays de la Loire region.
-
D.
Saintes
Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
-
E.
Bourges
Bourges is a historic city in central France known for its well-preserved medieval architecture and its UNESCO-listed Gothic cathedral, Saint-Étienne.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245467d9881908d6985bd0db7a1f1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1700edb608190ad786ff7fafea0da |
completed | April 29, 2026, 2:42 a.m. |
Created at: April 17, 2026, 3:03 p.m.