Triple

T11716724
Position Surface form Disambiguated ID Type / Status
Subject Cerdanya E278517 entity
Predicate borderedBy P224 FINISHED
Object Andorra E13377 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: Andorra | Statement: [Cerdanya, borderedBy, Andorra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Andorra
Context triple: [Cerdanya, borderedBy, Andorra]
  • A. Andorra chosen
    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.
  • B. 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.
  • C. Monaco
    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.
  • D. Luxembourg
    Luxembourg is a small, landlocked Western European country known for its prosperous economy, status as a major financial center, and role as a founding member of the European Union.
  • E. Liechtenstein
    Liechtenstein is a small, landlocked principality in Central Europe known for its alpine landscape, strong financial sector, and status as one of the world's wealthiest countries per capita.
  • 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_69d6aaff2ce88190b4a1e4b341ad5377 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a4c10d988190842acd824135cf15 completed April 10, 2026, 7:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef83a9479c81909cbe63d81255a1bf completed April 27, 2026, 3:41 p.m.
Created at: April 8, 2026, 9:40 p.m.