Triple
T20827704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belfry of Arras |
E512746
|
entity |
| Predicate | offersViewOf |
P3821
|
FINISHED |
| Object | Arras city center |
—
|
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: Arras city center | Statement: [Belfry of Arras, offersViewOf, Arras city center]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arras city center Context triple: [Belfry of Arras, offersViewOf, Arras city center]
-
A.
Arras
chosen
Arras is a historic city in northern France renowned for its Flemish-Baroque architecture, grand squares, and role as a strategic site in both World Wars.
-
B.
Porte d'Arras
Porte d'Arras is a metro station in Lille, France, serving the city's automated light metro network.
-
C.
Neufchâtel-sur-Aisne
Neufchâtel-sur-Aisne is a small commune in northern France situated along the Aisne River.
-
D.
City of Nancy
The City of Nancy is a historic city in northeastern France renowned for its elegant 18th-century architecture and UNESCO-listed squares.
-
E.
Péronne
Péronne is a historic town in northern France known for its role in World War I and its location in the Somme department.
- 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c31e387481909fcf323f97019803 |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:42 p.m.