Triple
T3498160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alpes-Maritimes |
E73900
|
entity |
| Predicate | containsCity |
P294
|
FINISHED |
| Object |
Carros
Carros is a commune in southeastern France situated in the Alpes-Maritimes department near Nice on the French Riviera.
|
E362735
|
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: Carros | Statement: [Alpes-Maritimes, containsCity, Carros]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carros Context triple: [Alpes-Maritimes, containsCity, Carros]
-
A.
Cars (franchise)
Cars (franchise) is a popular animated media and merchandise franchise created by Pixar and Disney, centered on anthropomorphic vehicles and best known for its feature films, spin-offs, and extensive toy lines.
-
B.
Cars (video game)
Cars (video game) is a racing and adventure title based on Pixar's animated film "Cars," allowing players to control characters like Lightning McQueen in story-driven and competitive driving events.
-
C.
CAR
CAR is a research center dedicated to advancing the understanding, diagnosis, and treatment of autism spectrum disorders through scientific study and clinical collaboration.
-
D.
CAR
CAR is the standard three-letter abbreviation used for the NFL team Carolina Panthers.
-
E.
CAR
CAR is the standard NHL abbreviation for the Carolina Hurricanes professional ice hockey team.
- 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: Carros Triple: [Alpes-Maritimes, containsCity, Carros]
Generated description
Carros is a commune in southeastern France situated in the Alpes-Maritimes department near Nice on the French Riviera.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Carros Target entity description: Carros is a commune in southeastern France situated in the Alpes-Maritimes department near Nice on the French Riviera.
-
A.
Cars (franchise)
Cars (franchise) is a popular animated media and merchandise franchise created by Pixar and Disney, centered on anthropomorphic vehicles and best known for its feature films, spin-offs, and extensive toy lines.
-
B.
Cars (video game)
Cars (video game) is a racing and adventure title based on Pixar's animated film "Cars," allowing players to control characters like Lightning McQueen in story-driven and competitive driving events.
-
C.
CAR
CAR is a research center dedicated to advancing the understanding, diagnosis, and treatment of autism spectrum disorders through scientific study and clinical collaboration.
-
D.
CAR
CAR is the standard three-letter abbreviation used for the NFL team Carolina Panthers.
-
E.
CAR
CAR is the standard NHL abbreviation for the Carolina Hurricanes professional ice hockey team.
- 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.