Triple
T18277790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Cergue |
E437782
|
entity |
| Predicate | hasLocality |
P7943
|
FINISHED |
| Object |
La Trélasse
La Trélasse is a small locality within the municipality of Saint-Cergue in the canton of Vaud, Switzerland.
|
E1315252
|
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: La Trélasse | Statement: [Saint-Cergue, hasLocality, La Trélasse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Trélasse Context triple: [Saint-Cergue, hasLocality, La Trélasse]
-
A.
Tournelle
Tournelle refers to the historical riverside district and former tower area in Paris that gave its name to the Pont de la Tournelle.
-
B.
La Passe
La Passe is the principal village and harbor area on La Digue Island in the Seychelles, serving as its main hub for transport, tourism, and local commerce.
-
C.
Canebière
Canebière is the historic main thoroughfare of Marseille, France, running from the Old Port into the city and long known as a bustling commercial and social hub.
-
D.
Les Brévières
Les Brévières is a traditional Alpine village and ski base within the Tignes resort area in the French Alps.
-
E.
Tignère
Tignère is a town and commune located in Cameroon's Adamawa Region, known for its highland setting and role as a local administrative and trading center.
- 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: La Trélasse Triple: [Saint-Cergue, hasLocality, La Trélasse]
Generated description
La Trélasse is a small locality within the municipality of Saint-Cergue in the canton of Vaud, Switzerland.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Trélasse Target entity description: La Trélasse is a small locality within the municipality of Saint-Cergue in the canton of Vaud, Switzerland.
-
A.
Tournelle
Tournelle refers to the historical riverside district and former tower area in Paris that gave its name to the Pont de la Tournelle.
-
B.
La Passe
La Passe is the principal village and harbor area on La Digue Island in the Seychelles, serving as its main hub for transport, tourism, and local commerce.
-
C.
Canebière
Canebière is the historic main thoroughfare of Marseille, France, running from the Old Port into the city and long known as a bustling commercial and social hub.
-
D.
Les Brévières
Les Brévières is a traditional Alpine village and ski base within the Tignes resort area in the French Alps.
-
E.
Tignère
Tignère is a town and commune located in Cameroon's Adamawa Region, known for its highland setting and role as a local administrative and trading center.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50053cc808190b46a3ec9d96936fe |
completed | April 19, 2026, 4:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03b3ffe1508190948d41bed9853a3e |
completed | May 12, 2026, 11:13 p.m. |
| NEDg | Description generation | batch_6a03b4bb6ae48190a68c2a3314f0d3ba |
completed | May 12, 2026, 11:16 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03b56958a0819088613a9726c71819 |
completed | May 12, 2026, 11:19 p.m. |
Created at: April 10, 2026, 10:34 a.m.