Triple
T6393430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heineken France |
E143883
|
entity |
| Predicate | brandManaged |
P42952
|
FINISHED |
| Object | Affligem |
E583481
|
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: Affligem | Statement: [Heineken France, brandManaged, Affligem]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Affligem Context triple: [Heineken France, brandManaged, Affligem]
-
A.
Affligem
chosen
Affligem is a historic Belgian abbey beer brand known for its traditional brewing heritage and distinctive ales.
-
B.
Eembrugge
Eembrugge is a small hamlet in the Dutch province of Utrecht, known for its rural character and location near the River Eem.
-
C.
Margraten
Margraten is a village in the Dutch province of Limburg best known for hosting the Netherlands American Cemetery, a major World War II military burial ground for U.S. soldiers.
-
D.
Warffum
Warffum is a historic village in the Dutch province of Groningen, known for its traditional architecture and open-air museum showcasing rural life.
-
E.
Cureghem
Cureghem is a historically working-class, multicultural neighborhood in the Brussels municipality of Anderlecht, known for its dense urban fabric and industrial heritage.
- 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_69c008db906c819096f3597d55d95432 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0687f5c6c81909c835329c996b311 |
completed | March 22, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6388f42648190adbc2d1c1efa75a5 |
completed | March 27, 2026, 7:58 a.m. |
Created at: March 22, 2026, 4:34 p.m.