Triple
T19989012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert of Arbrissel |
E494009
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Arbrissel |
—
|
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: Arbrissel | Statement: [Robert of Arbrissel, placeOfBirth, Arbrissel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arbrissel Context triple: [Robert of Arbrissel, placeOfBirth, Arbrissel]
-
A.
Binche
Binche is a historic town in the Walloon region of Belgium, renowned for its well-preserved medieval architecture and its UNESCO-recognized Carnival of Binche.
-
B.
Nivelles
Nivelles is a historic town in present-day Belgium known for its medieval architecture, including the Romanesque Collegiate Church of Saint Gertrude.
-
C.
Durbuy
Durbuy is a small, picturesque town in the Belgian Ardennes often promoted as one of the “smallest cities in the world,” known for its medieval architecture and tourism.
-
D.
Moringhem
chosen
Moringhem is a small commune in northern France, located in the Pas-de-Calais department within the Hauts-de-France region.
-
E.
Gosselies
Gosselies is a district of the city of Charleroi in Wallonia, Belgium, known for its proximity to Brussels South Charleroi Airport and its industrial and aeronautical activities.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fddfee081909aa8cd6e279b2a7a |
completed | April 20, 2026, 5:18 p.m. |
Created at: April 11, 2026, 3:30 p.m.