Triple

T14106169
Position Surface form Disambiguated ID Type / Status
Subject TF1 E339510 entity
Predicate broadcastArea P2441 FINISHED
Object Monaco E18404 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: Monaco | Statement: [TF1, broadcastArea, Monaco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Monaco
Context triple: [TF1, broadcastArea, Monaco]
  • A. Monaco
    Monaco was the original name of Crypto.com, a cryptocurrency and financial services platform known for its crypto-backed payment cards and trading app.
  • B. Monaco chosen
    Monaco is a small sovereign city-state on the French Riviera known for its wealth, luxury tourism, and status as a major tax haven and gambling hub.
  • C. AS Monaco
    AS Monaco is a prominent football club based in the Principality of Monaco, known for competing in France's top division and developing numerous world-class players.
  • D. Andorra
    Andorra is a small, landlocked principality in the eastern Pyrenees between France and Spain, known for its mountainous terrain, tourism, and status as a tax haven.
  • E. San Marino
    San Marino is a small, landlocked microstate surrounded by Italy, known as one of the world’s oldest republics and a popular tourist destination.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de600ada808190b92d67dc30f13d15 completed April 14, 2026, 3:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcd0b48e448190b4fb8cb33e5d97e6 completed May 7, 2026, 5:49 p.m.
Created at: April 9, 2026, 10:22 p.m.