Triple
T6113812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Matilda I of Boulogne |
E136310
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Boulogne |
E122723
|
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: Boulogne | Statement: [Matilda I of Boulogne, placeOfBirth, Boulogne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Boulogne Context triple: [Matilda I of Boulogne, placeOfBirth, Boulogne]
-
A.
Boulogne-sur-Mer
chosen
Boulogne-sur-Mer is a coastal city and major fishing port in northern France, located on the English Channel in the Pas-de-Calais department.
-
B.
Boulogne-sur-Seine
Boulogne-sur-Seine was a former commune in the western suburbs of Paris, France, now part of Boulogne-Billancourt, known historically as a residential and industrial area along the Seine River.
-
C.
Pont-l’Évêque
Pont-l’Évêque is a small historic town in Normandy, France, best known for giving its name to the traditional soft cow’s milk cheese Pont-l’Évêque.
-
D.
Cherbourg
Cherbourg is a major French port city on the Cotentin Peninsula, known for its strategic naval harbor and cross-Channel ferry connections.
-
E.
Montreuil-sur-Mer
Montreuil-sur-Mer is a small historic town in northern France, notably serving as a key setting in Victor Hugo’s novel "Les Misérables."
- 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_69c0089ea6f88190b349be53e04b4f5f |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05bbf2ee4819097af2cce9248bf4e |
completed | March 22, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1359ed8608190a99c9e5b0f384c63 |
completed | March 23, 2026, 12:44 p.m. |
Created at: March 22, 2026, 4:14 p.m.