Triple

T8939643
Position Surface form Disambiguated ID Type / Status
Subject Elche E212865 entity
Predicate nearbyCity P350 FINISHED
Object Murcia E49762 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: Murcia | Statement: [Elche, nearbyCity, Murcia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Murcia
Context triple: [Elche, nearbyCity, Murcia]
  • A. Murcia chosen
    Murcia is a historic city and region in southeastern Spain, known for its fertile agricultural plain, baroque architecture, and role as a former frontier territory between Christian and Muslim realms on the Iberian Peninsula.
  • B. Jaén
    Jaén is a province in southern Spain’s Andalusia region, renowned for its vast olive groves and historic Renaissance towns.
  • C. Jaén
    Jaén is a significant commercial and agricultural city in northern Peru, known as a regional hub within the Cajamarca Region.
  • D. Almería
    Almería is a coastal city and province in southeastern Spain known for its arid climate, historic Alcazaba fortress, and extensive greenhouse agriculture.
  • E. Jaen
    Jaen is a landlocked agricultural municipality in the province of Nueva Ecija in the Central Luzon region of the Philippines.
  • 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_69ca839694c88190b324ffeb43d23b08 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc66b7484481909e0d7610552f5386 completed April 1, 2026, 12:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69d178b408c8819080cd15c1efcd7002 completed April 4, 2026, 8:46 p.m.
Created at: March 30, 2026, 6:58 p.m.