Triple
T3498176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpes-Maritimes |
E73900
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Aspremont
Aspremont is a small picturesque commune in southeastern France, situated in the hills above Nice in the Alpes-Maritimes department.
|
E362748
|
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: Aspremont | Statement: [Alpes-Maritimes, containsCity, Aspremont]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aspremont Context triple: [Alpes-Maritimes, containsCity, Aspremont]
-
A.
Rocard
Rocard is a French surname most notably associated with Michel Rocard, a former Prime Minister of France and prominent Socialist politician.
-
B.
Jeanneret
Jeanneret is a Swiss surname most notably associated with architect Pierre Jeanneret, a key collaborator of Le Corbusier in modernist architecture.
-
C.
Breuillet
Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
-
D.
Lasserre
Lasserre is a small rural commune in southwestern France known for being the later-life home of the influential mathematician Alexander Grothendieck.
-
E.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
- 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: Aspremont Triple: [Alpes-Maritimes, containsCity, Aspremont]
Generated description
Aspremont is a small picturesque commune in southeastern France, situated in the hills above Nice in the Alpes-Maritimes department.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Aspremont Target entity description: Aspremont is a small picturesque commune in southeastern France, situated in the hills above Nice in the Alpes-Maritimes department.
-
A.
Rocard
Rocard is a French surname most notably associated with Michel Rocard, a former Prime Minister of France and prominent Socialist politician.
-
B.
Jeanneret
Jeanneret is a Swiss surname most notably associated with architect Pierre Jeanneret, a key collaborator of Le Corbusier in modernist architecture.
-
C.
Breuillet
Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
-
D.
Lasserre
Lasserre is a small rural commune in southwestern France known for being the later-life home of the influential mathematician Alexander Grothendieck.
-
E.
Lebrun
Lebrun is a French surname borne by various notable figures in politics, arts, and other fields.
- 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_69ad85cdb6e48190a335d412b9194ed8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbd299ec8190b76b165b2fd70537 |
completed | March 8, 2026, 6:11 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b373d011c0819088245afe03be3c44 |
completed | March 13, 2026, 2:17 a.m. |
| NEDg | Description generation | batch_69b3745c7304819085a47af79cd738c0 |
completed | March 13, 2026, 2:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b374f5999c8190ae48570a412dc6dc |
completed | March 13, 2026, 2:22 a.m. |
Created at: March 8, 2026, 3:18 p.m.