Triple

T9751531
Position Surface form Disambiguated ID Type / Status
Subject Dark E236452 entity
Predicate director P255 FINISHED
Object Baran bo Odar E818075 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: Baran bo Odar | Statement: [Dark, director, Baran bo Odar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Baran bo Odar
Context triple: [Dark, director, Baran bo Odar]
  • A. Baran bo Odar chosen
    Baran bo Odar is a Swiss film and television director and screenwriter best known for co-creating and directing the acclaimed German sci-fi thriller series "Dark."
  • B. Loggal Oya
    Loggal Oya is a river in Sri Lanka that serves as one of the tributaries feeding the country’s longest river system.
  • C. Baran
    Baran is a surname most notably associated with Paul Baran, a pioneering engineer of packet-switched networks and early internet technology.
  • D. Baran
    Baran is a city in the Hadoti region of Rajasthan, India, known for its historical temples, forts, and proximity to natural attractions like waterfalls and wildlife sanctuaries.
  • E. Barcha
    Barcha is the surname of Mercedes Barcha, the Colombian wife and lifelong companion of Nobel Prize–winning author Gabriel García Márquez.
  • 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_69ca84d4eddc8190996fec1417d2bae8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9facd5b881909f0569b23f308815 completed April 1, 2026, 10:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcd60e1c81908ea2e38ca91e58f6 completed April 5, 2026, 1:37 a.m.
Created at: March 30, 2026, 8:24 p.m.