Triple
T22265109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Vaison-la-Romaine |
E550330
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Travaillan
Travaillan is a small commune in the Vaucluse department of southeastern France, known for its rural Provençal setting.
|
E1527787
|
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: Travaillan | Statement: [canton of Vaison-la-Romaine, contains, Travaillan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Travaillan Context triple: [canton of Vaison-la-Romaine, contains, Travaillan]
-
A.
Dagneux
Dagneux is a commune in eastern France’s Ain department, known for its residential character and proximity to the Lyon metropolitan area.
-
B.
Bévilard
Bévilard is a village in the Bernese Jura region of the canton of Bern in Switzerland.
-
C.
Tilleur
Tilleur is a district of the Belgian municipality of Saint-Nicolas in the province of Liège, known historically for its industrial and steelmaking activities.
-
D.
Berlare
Berlare is a municipality in the East Flanders province of Belgium, known for its rural character and proximity to the Donkmeer lake and nature reserve.
-
E.
Tergnier
Tergnier is a commune in northern France known historically as a significant railway junction and industrial town in the Aisne department.
- 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: Travaillan Triple: [canton of Vaison-la-Romaine, contains, Travaillan]
Generated description
Travaillan is a small commune in the Vaucluse department of southeastern France, known for its rural Provençal setting.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Travaillan Target entity description: Travaillan is a small commune in the Vaucluse department of southeastern France, known for its rural Provençal setting.
-
A.
Dagneux
Dagneux is a commune in eastern France’s Ain department, known for its residential character and proximity to the Lyon metropolitan area.
-
B.
Bévilard
Bévilard is a village in the Bernese Jura region of the canton of Bern in Switzerland.
-
C.
Tilleur
Tilleur is a district of the Belgian municipality of Saint-Nicolas in the province of Liège, known historically for its industrial and steelmaking activities.
-
D.
Berlare
Berlare is a municipality in the East Flanders province of Belgium, known for its rural character and proximity to the Donkmeer lake and nature reserve.
-
E.
Tergnier
Tergnier is a commune in northern France known historically as a significant railway junction and industrial town in the Aisne department.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141bb850881908f5e9c37afb52ca8 |
completed | April 28, 2026, 11:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0ab66c7f248190be0b13342f843eb8 |
completed | May 18, 2026, 6:49 a.m. |
| NEDg | Description generation | batch_6a0ab7b53aa881908227842536d7e8cc |
completed | May 18, 2026, 6:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0ab82b5a988190a55dd87f10664821 |
completed | May 18, 2026, 6:56 a.m. |
Created at: April 16, 2026, 8:39 p.m.