Triple
T14145510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Place Masséna |
E350537
|
entity |
| Predicate | governingBody |
P46
|
FINISHED |
| Object | City of Nice |
E140630
|
NE FINISHED |
How this triple was built (2 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: City of Nice | Statement: [Place Masséna, governingBody, City of Nice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Nice Context triple: [Place Masséna, governingBody, City of Nice]
-
A.
City of Nice
chosen
The City of Nice is a major coastal city on the French Riviera, renowned for its Mediterranean climate, historic old town, and rich artistic and cultural heritage.
-
B.
Vieux-Nice
Vieux-Nice is the historic old town of Nice, France, known for its narrow winding streets, colorful buildings, bustling markets, and vibrant Mediterranean atmosphere.
-
C.
Grasse
Grasse is a town in southeastern France renowned as the world’s perfume capital and a historic center of the fragrance industry.
-
D.
Villefranche-sur-Mer
Villefranche-sur-Mer is a picturesque coastal town in southeastern France known for its deep natural harbor, colorful old town, and scenic setting on the Mediterranean Sea.
-
E.
Old Town (Vieux-Nice)
Old Town (Vieux-Nice) is the historic quarter of Nice, France, known for its narrow winding streets, colorful facades, bustling markets, and vibrant Mediterranean atmosphere.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d827865f608190b311820428ae027b |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de612266248190a8591b646fe30ae6 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd324531c88190abab2092d1f7145d |
completed | May 8, 2026, 12:45 a.m. |
Created at: April 10, 2026, 12:53 a.m.