Triple
T9215197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | canton of Vence |
E221224
|
entity |
| Predicate | containsCommune |
P15149
|
FINISHED |
| Object |
Gilette
Gilette is a small French commune in the Alpes-Maritimes department of southeastern France, known for its hilltop setting overlooking the confluence of the Var and Estéron rivers.
|
E785571
|
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: Gilette | Statement: [canton of Vence, containsCommune, Gilette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gilette Context triple: [canton of Vence, containsCommune, Gilette]
-
A.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
-
B.
Braun
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
C.
Ansell
Ansell is a minor character in the adventure video game "The Longest Journey," appearing as part of its richly detailed narrative world.
-
D.
Philipse
Philipse is the surname of a prominent colonial-era merchant and landowning family in what is now New York, notably associated with Frederick Philipse I.
-
E.
Henkel
Henkel is a German multinational chemical and consumer goods company best known for its brands in laundry, home care, and adhesives.
- 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: Gilette Triple: [canton of Vence, containsCommune, Gilette]
Generated description
Gilette is a small French commune in the Alpes-Maritimes department of southeastern France, known for its hilltop setting overlooking the confluence of the Var and Estéron rivers.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gilette Target entity description: Gilette is a small French commune in the Alpes-Maritimes department of southeastern France, known for its hilltop setting overlooking the confluence of the Var and Estéron rivers.
-
A.
Gillette
Gillette is a globally recognized American brand best known for its razors and shaving products.
-
B.
Braun
Braun is a German surname most infamously associated with Eva Braun, the longtime companion and brief wife of Adolf Hitler.
-
C.
Ansell
Ansell is a minor character in the adventure video game "The Longest Journey," appearing as part of its richly detailed narrative world.
-
D.
Philipse
Philipse is the surname of a prominent colonial-era merchant and landowning family in what is now New York, notably associated with Frederick Philipse I.
-
E.
Henkel
Henkel is a German multinational chemical and consumer goods company best known for its brands in laundry, home care, and adhesives.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda0830a8819096a186ed2e976cba |
completed | April 1, 2026, 8:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0661c4c2c8190bc5be991a3a75f2b |
completed | April 4, 2026, 1:15 a.m. |
| NEDg | Description generation | batch_69d0678b89ac8190b807e1c3b457a503 |
completed | April 4, 2026, 1:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0688d4c388190bb024b03cc86d08f |
completed | April 4, 2026, 1:25 a.m. |
Created at: March 30, 2026, 7:27 p.m.