Triple

T21205385
Position Surface form Disambiguated ID Type / Status
Subject Bersenbrück E522563 entity
Predicate locatedOnRiver P165 FINISHED
Object Hase NE NERFINISHED

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: Hase | Statement: [Bersenbrück, locatedOnRiver, Hase]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hase
Context triple: [Bersenbrück, locatedOnRiver, Hase]
  • A. Hase chosen
    The Hase is a river in northwestern Germany that flows through Lower Saxony and North Rhine-Westphalia, passing towns such as Quakenbrück before joining the Ems.
  • B. Haise
    Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
  • C. Hane
    Hane is a small coastal village on the Marquesan island of Ua Huka in French Polynesia, known for its archaeological sites and traditional Polynesian culture.
  • D. Hagus
    Hagus is a small settlement located on Buka Island in the Autonomous Region of Bougainville, Papua New Guinea.
  • E. Harku
    Harku is a small settlement in northern Estonia located within Harku Parish, near the capital city of Tallinn.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b5112d8881909510b2dcdc93106d completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e734342e9081909e241bed54dbc0b4 completed April 21, 2026, 8:24 a.m.
Created at: April 16, 2026, 3:20 p.m.