Triple

T4676239
Position Surface form Disambiguated ID Type / Status
Subject Pozuelo de Alarcón E103687 entity
Predicate hasNeighbour P5707 FINISHED
Object Alcorcón E95939 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: Alcorcón | Statement: [Pozuelo de Alarcón, hasNeighbour, Alcorcón]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alcorcón
Context triple: [Pozuelo de Alarcón, hasNeighbour, Alcorcón]
  • A. Alcorcón chosen
    Alcorcón is a suburban city in central Spain that forms part of the metropolitan area of Madrid.
  • B. Móstoles
    Móstoles is a major suburban city in central Spain, known as one of the most populous municipalities in the Madrid metropolitan area.
  • C. Vallecas
    Vallecas is a district in the southeast of Madrid, Spain, known for its working-class roots, strong local identity, and vibrant community life.
  • D. Leganés
    Leganés is a major suburban city in central Spain, located just southwest of Madrid and known for its residential character, industry, and football club CD Leganés.
  • E. Fuenlabrada
    Fuenlabrada is a large suburban city in central Spain, located southwest of Madrid and known for its rapid growth, industrial activity, and sizable commuter population.
  • 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_69bd43dda32c8190938b37744ca270fc completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd63685cb88190ac1904e2c7eb6b61 completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be104e4aec8190a633b46eca1f434b completed March 21, 2026, 3:28 a.m.
Created at: March 20, 2026, 1:16 p.m.