Triple

T1089875
Position Surface form Disambiguated ID Type / Status
Subject Tagus River E24137 entity
Predicate nameInSpanish P2789 FINISHED
Object Tajo E118542 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: Tajo | Statement: [Tagus River, nameInSpanish, Tajo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tajo
Context triple: [Tagus River, nameInSpanish, Tajo]
  • A. Cieneguilla
    Cieneguilla is a semi-rural district in the eastern part of Lima, Peru, known for its natural landscapes, country houses, and outdoor recreation areas.
  • B. Tajo River chosen
    The Tajo River is the longest river on the Iberian Peninsula, flowing from eastern Spain through central regions into Portugal before emptying into the Atlantic Ocean.
  • C. Terevaka
    Terevaka is a large extinct volcanic peak that forms the highest and youngest of the three main volcanoes making up Easter Island.
  • D. Magdalena
    Magdalena is the given first name of Swedish opera singer and environmental activist Malena Ernman.
  • E. Ranna
    Ranna was a prominent 10th-century Kannada poet, celebrated as one of the “three gems” of early Kannada literature for his influential epic and courtly works.
  • 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_69a49404428c819092dcc9632f5f7b8b completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b97f216881909e9b8943ce2078e4 completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac4c2a20b48190b3a550f6e5ee13e1 completed March 7, 2026, 4:02 p.m.
Created at: March 1, 2026, 7:42 p.m.