Triple

T1303185
Position Surface form Disambiguated ID Type / Status
Subject Manzanares River E27813 entity
Predicate flowsThrough P225 FINISHED
Object Getafe E92560 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: Getafe | Statement: [Manzanares River, flowsThrough, Getafe]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Getafe
Context triple: [Manzanares River, flowsThrough, Getafe]
  • A. Getafe chosen
    Getafe is a city in central Spain that forms part of the Madrid metropolitan area and is known for its industrial base, university campus, and air force history.
  • B. Alcorcón
    Alcorcón is a suburban city in central Spain that forms part of the metropolitan area of Madrid.
  • C. 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.
  • D. 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.
  • E. Móstoles
    Móstoles is a major suburban city in central Spain, known as one of the most populous municipalities in the Madrid metropolitan area.
  • 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_69a496d7d83481908f83085854e51328 completed March 1, 2026, 7:43 p.m.
NER Named-entity recognition batch_69a4c116d7d881908ee631258f80980e completed March 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69acb3046a888190956f6bedb6ec589f completed March 7, 2026, 11:21 p.m.
Created at: March 1, 2026, 7:51 p.m.