Triple

T13635337
Position Surface form Disambiguated ID Type / Status
Subject Greater Zürich Area E325833 entity
Predicate hasMajorRiver P165 FINISHED
Object Limmat E70156 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: Limmat | Statement: [Greater Zürich Area, hasMajorRiver, Limmat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limmat
Context triple: [Greater Zürich Area, hasMajorRiver, Limmat]
  • A. Limmat chosen
    The Limmat is a Swiss river that flows out of Lake Zurich through the city of Zurich and continues northward until it joins the Aare.
  • B. Laimosemion
    Laimosemion is a genus of small, brightly colored Neotropical killifishes commonly found in freshwater habitats of northern South America.
  • C. Malili
    Malili is a town in South Sulawesi, Indonesia, serving as the administrative and economic center of East Luwu Regency.
  • D. Luntai
    Luntai is a small oasis town and county in China’s Xinjiang region, situated along the northern edge of the Taklamakan Desert on the historic Silk Road.
  • E. Lupaus
    Lupaus is a Finnish film for which composer Tuomas Kantelinen created the musical score.
  • 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_69d8076beddc8190a53156f5bea77f5e completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc5a616dc81908b8c1213e1d4beed completed April 12, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78aef6fd08190b209a94b9ddd024c completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:51 p.m.