Triple

T21298565
Position Surface form Disambiguated ID Type / Status
Subject Bregenz Forest Mountains E524992 entity
Predicate drainage P1559 FINISHED
Object Subersach 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: Subersach | Statement: [Bregenz Forest Mountains, drainage, Subersach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Subersach
Context triple: [Bregenz Forest Mountains, drainage, Subersach]
  • A. Subersach chosen
    Subersach is a river in the Austrian state of Vorarlberg that flows through the Bregenzerwald region before joining the Bregenzer Ach.
  • B. Sambir
    Sambir is a small historic city in western Ukraine known for its medieval roots and location within the Lviv Oblast.
  • C. Sancar
    Sancar is the surname of Aziz Sancar, a Turkish-American biochemist and molecular biologist renowned for his Nobel Prize–winning work on DNA repair.
  • D. Sahpresa
    Sahpresa is a high-class Thoroughbred racehorse best known for winning multiple editions of the Group 1 Sun Chariot Stakes in England.
  • E. Sarachei
    Sarachei is a small settlement located within the municipality of Kalampaka in the Thessaly region of Greece.
  • 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385a24d08190bfd410c7f10fa6f7 completed April 21, 2026, 8:42 a.m.
Created at: April 16, 2026, 4:04 p.m.