Triple
T13048486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Condroz |
E327385
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Lobbes
Lobbes is a historic municipality in the Walloon region of Belgium, known for its ancient abbey and picturesque rural setting.
|
E1018280
|
NE FINISHED |
How this triple was built (4 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: Lobbes | Statement: [Condroz, containsSettlement, Lobbes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lobbes Context triple: [Condroz, containsSettlement, Lobbes]
-
A.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
-
B.
Beaufays
Beaufays is a village in the municipality of Chaudfontaine in the province of Liège, Belgium.
-
C.
Villeblevin
Villeblevin is a small commune in north-central France, best known as the place where writer Albert Camus died in a car accident.
-
D.
Löwenberg
Löwenberg is a town in Germany known for its cultural and municipal partnership as a twin town of Weilburg.
-
E.
Bricmont
Bricmont is a surname most notably associated with American film editor Wendy Greene Bricmont.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lobbes Triple: [Condroz, containsSettlement, Lobbes]
Generated description
Lobbes is a historic municipality in the Walloon region of Belgium, known for its ancient abbey and picturesque rural setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lobbes Target entity description: Lobbes is a historic municipality in the Walloon region of Belgium, known for its ancient abbey and picturesque rural setting.
-
A.
Lübars
Lübars is a historic, village-like district in Berlin’s Reinickendorf borough, known for its rural character, fields, and preserved traditional architecture within the city.
-
B.
Beaufays
Beaufays is a village in the municipality of Chaudfontaine in the province of Liège, Belgium.
-
C.
Villeblevin
Villeblevin is a small commune in north-central France, best known as the place where writer Albert Camus died in a car accident.
-
D.
Löwenberg
Löwenberg is a town in Germany known for its cultural and municipal partnership as a twin town of Weilburg.
-
E.
Bricmont
Bricmont is a surname most notably associated with American film editor Wendy Greene Bricmont.
- F. None of above. chosen
Provenance (5 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_69d8076e64308190904fb5c93517c901 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980b8811c81908577f092e2736610 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6cbd8f1308190992c0bd832e1b05e |
completed | May 3, 2026, 4:15 a.m. |
| NEDg | Description generation | batch_69f6cd98d29c8190b33cb2cc6c477b1d |
completed | May 3, 2026, 4:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6ce23ca208190960409130c4c52a9 |
completed | May 3, 2026, 4:25 a.m. |
Created at: April 9, 2026, 8:57 p.m.