Triple
T10619526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannut |
E295670
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object |
Petit-Hallet
Petit-Hallet is a small village in the municipality of Hannut in the province of Liège, Belgium.
|
E875496
|
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: Petit-Hallet | Statement: [Hannut, hasSubdivision, Petit-Hallet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Petit-Hallet Context triple: [Hannut, hasSubdivision, Petit-Hallet]
-
A.
Les Breuleux
Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
-
B.
Petitpierre
Petitpierre is a historical publishing house known for issuing scientific works, including influential 19th-century studies on fossil fishes.
-
C.
Orléat
Orléat is a small commune in central France’s Puy-de-Dôme department, known for its rural character within the Auvergne region.
-
D.
Nantouillet
Nantouillet is a small rural commune in the Seine-et-Marne department in the Île-de-France region of north-central France.
-
E.
Léchelles
Léchelles is a village and former municipality in the canton of Fribourg in western Switzerland.
- 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: Petit-Hallet Triple: [Hannut, hasSubdivision, Petit-Hallet]
Generated description
Petit-Hallet is a small village in the municipality of Hannut in the province of Liège, Belgium.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Petit-Hallet Target entity description: Petit-Hallet is a small village in the municipality of Hannut in the province of Liège, Belgium.
-
A.
Les Breuleux
Les Breuleux is a small Swiss municipality and village in the Jura region, known for its watchmaking tradition and rural alpine setting.
-
B.
Petitpierre
Petitpierre is a historical publishing house known for issuing scientific works, including influential 19th-century studies on fossil fishes.
-
C.
Orléat
Orléat is a small commune in central France’s Puy-de-Dôme department, known for its rural character within the Auvergne region.
-
D.
Nantouillet
Nantouillet is a small rural commune in the Seine-et-Marne department in the Île-de-France region of north-central France.
-
E.
Léchelles
Léchelles is a village and former municipality in the canton of Fribourg in western Switzerland.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d6df6fc47c8190b77b61a7fd223d65 |
completed | April 8, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d96b86a5bc8190863034cc91fdbbb9 |
completed | April 10, 2026, 9:28 p.m. |
| NEDg | Description generation | batch_69d96def8bfc81909d6a5addf724691b |
completed | April 10, 2026, 9:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d96fedb18881908570593856f4aade |
completed | April 10, 2026, 9:47 p.m. |
Created at: April 8, 2026, 8:21 p.m.