Triple
T16288915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thérouanne Cathedral |
E395465
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | Thérouanne |
E395464
|
NE 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: Thérouanne | Statement: [Thérouanne Cathedral, namedAfter, Thérouanne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Thérouanne Context triple: [Thérouanne Cathedral, namedAfter, Thérouanne]
-
A.
Thérouanne
chosen
Thérouanne is a historic town in northern France that once served as an important medieval religious center and episcopal seat.
-
B.
Arras
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.
-
C.
Cambrai
Cambrai is a historic city in northern France known for its medieval heritage, role in World War I, and traditional confectionery.
-
D.
Landrecies
Landrecies is a small commune in northern France, historically part of the fortified border region of French Flanders.
-
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 (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_69d87f22c7248190a54c949738441e2e |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e249165af881908ce44c4517c93c12 |
completed | April 17, 2026, 2:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f3d8f188190969b75d82c6b13f0 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:05 a.m.