Triple
T3110523
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vosges Mountains |
E64937
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object |
Gérardmer
Gérardmer is a picturesque lakeside town in northeastern France known for its ski resort, natural scenery, and annual fantasy film festival.
|
E363737
|
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: Gérardmer | Statement: [Vosges Mountains, hasTown, Gérardmer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gérardmer Context triple: [Vosges Mountains, hasTown, Gérardmer]
-
A.
Thonon-les-Bains
Thonon-les-Bains is a French spa and resort town in the Haute-Savoie region, known for its lakeside setting on Lake Geneva and views of the Alps.
-
B.
Bilhères
Bilhères is a small mountain village in southwestern France, situated in the Ossau Valley of the Pyrenees.
-
C.
Voiron
Voiron is a commune in southeastern France known for its historical town center and proximity to the Chartreuse Mountains.
-
D.
Brioude
Brioude is a historic town in south-central France known for its Romanesque Basilica of Saint-Julien and its location in the Haute-Loire department of the Auvergne region.
-
E.
Gueugnon
Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
- 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: Gérardmer Triple: [Vosges Mountains, hasTown, Gérardmer]
Generated description
Gérardmer is a picturesque lakeside town in northeastern France known for its ski resort, natural scenery, and annual fantasy film festival.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gérardmer Target entity description: Gérardmer is a picturesque lakeside town in northeastern France known for its ski resort, natural scenery, and annual fantasy film festival.
-
A.
Thonon-les-Bains
Thonon-les-Bains is a French spa and resort town in the Haute-Savoie region, known for its lakeside setting on Lake Geneva and views of the Alps.
-
B.
Bilhères
Bilhères is a small mountain village in southwestern France, situated in the Ossau Valley of the Pyrenees.
-
C.
Voiron
Voiron is a commune in southeastern France known for its historical town center and proximity to the Chartreuse Mountains.
-
D.
Brioude
Brioude is a historic town in south-central France known for its Romanesque Basilica of Saint-Julien and its location in the Haute-Loire department of the Auvergne region.
-
E.
Gueugnon
Gueugnon is a small commune in eastern France known historically for its steel industry and location in the Bourgogne-Franche-Comté region.
- 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_69ad857eeaf48190b34ebfdaa7a264cf |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada437c5e08190af22f6fa11cf9252 |
completed | March 8, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373888b948190b84d7bfa908f15ad |
completed | March 13, 2026, 2:16 a.m. |
| NEDg | Description generation | batch_69b3776ecca481908885e3c948b3a9f1 |
completed | March 13, 2026, 2:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b377d036988190a8a17fbffe298844 |
completed | March 13, 2026, 2:34 a.m. |
Created at: March 8, 2026, 3:04 p.m.