Triple

T16394622
Position Surface form Disambiguated ID Type / Status
Subject The Green House E398146 entity
Predicate hasTitleInOriginalLanguage P13516 FINISHED
Object La casa verde E398145 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: La casa verde | Statement: [The Green House, hasTitleInOriginalLanguage, La casa verde]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La casa verde
Context triple: [The Green House, hasTitleInOriginalLanguage, La casa verde]
  • A. La casa verde chosen
    La casa verde is a landmark novel by Peruvian writer Mario Vargas Llosa that intertwines multiple narratives to explore corruption, desire, and social conflict in mid-20th-century Peru.
  • B. The Green Place
    The Green Place is a once-fertile, now-lost oasis homeland of the Vuvalini in the post-apocalyptic world of the film "Mad Max: Fury Road."
  • C. The Green
    The Green is a historic central park and community gathering space located in downtown Morristown, New Jersey.
  • D. The Green
    The Green is a historic central public square in Dover, Delaware, known for its colonial-era buildings and role in early American political and civic life.
  • E. The Green
    The Green is a small rural settlement in Cumbria, England, situated near the town of Millom in the southwestern Lake District 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e3264538e4819082442d254accf392 completed April 18, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c58280081908e4d73a75b09dbb8 completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:08 a.m.