Triple

T7657817
Position Surface form Disambiguated ID Type / Status
Subject Helsingborg E173429 entity
Predicate hasTwinTown P919 FINISHED
Object Palma de Mallorca E144499 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: Palma de Mallorca | Statement: [Helsingborg, hasTwinTown, Palma de Mallorca]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palma de Mallorca
Context triple: [Helsingborg, hasTwinTown, Palma de Mallorca]
  • A. Palma de Mallorca chosen
    Palma de Mallorca is the historic coastal city and major tourist destination that serves as the political, cultural, and economic center of Spain’s Balearic Islands.
  • B. Palma
    Palma is a Spanish-origin surname borne by various notable individuals across the Spanish-speaking world and beyond.
  • C. Benidorm
    Benidorm is a major Spanish Mediterranean resort city famous for its skyscraper-lined beaches, vibrant nightlife, and mass tourism.
  • D. Marbella
    Marbella is a popular resort city on Spain’s Costa del Sol, known for its Mediterranean beaches, luxury marinas, upscale nightlife, and historic old town.
  • E. Mahón
    Mahón is the principal city and administrative center of the Spanish Balearic island of Menorca, known for its large natural harbor and historic architecture.
  • 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7019161548190855a5b1e9f5d7e99 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c89b0d345081909a1d4475fa3876f5 completed March 29, 2026, 3:22 a.m.
Created at: March 27, 2026, 3:59 p.m.