Triple
T8959554
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brabant |
E213565
|
entity |
| Predicate | sharesBorderWith |
P224
|
FINISHED |
| Object | Hainaut |
E86438
|
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: Hainaut | Statement: [Brabant, sharesBorderWith, Hainaut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hainaut Context triple: [Brabant, sharesBorderWith, Hainaut]
-
A.
Hainaut
chosen
Hainaut is a historical region in western Europe, now divided between Belgium and France, known for its medieval heritage and role as a frequent battleground in European conflicts.
-
B.
Putot-en-Bessin
Putot-en-Bessin is a small commune in the Calvados department of Normandy in northwestern France, known for its rural character and World War II history.
-
C.
Cernières
Cernières is a small locality situated within the canton of Breteuil in northern France.
-
D.
Brionnais
Brionnais is a historic rural region in eastern France known for its Romanesque churches, traditional stone villages, and Charolais cattle farming.
-
E.
Langrois
Langrois is the French term for an inhabitant or native of the town of Langres in northeastern France.
- 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_69ca8399ad2081909f8fa41d4314c215 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc672b12b48190a9d964f79b96d237 |
completed | April 1, 2026, 12:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc946a2f88190b7cd0fca67d31dfd |
completed | April 3, 2026, 2:05 p.m. |
Created at: March 30, 2026, 7 p.m.