Triple

T3700332
Position Surface form Disambiguated ID Type / Status
Subject Sihl River E78561 entity
Predicate riverSystem P1009 FINISHED
Object Limmat river system E118490 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 river system | Statement: [Sihl River, riverSystem, Limmat river system]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Limmat river system
Context triple: [Sihl River, riverSystem, Limmat river system]
  • A. Limmat River chosen
    The Limmat River is a major Swiss waterway that flows out of Lake Zurich and runs through the city of Zurich before joining the Aare River.
  • B. Sakmara River
    The Sakmara River is a major river in Russia that flows through the southern Ural region before joining the Ural River.
  • C. Musi River
    The Musi River is a significant river in the Deccan region of India that flows through the city of Hyderabad, historically shaping its development and water supply.
  • D. Musi River
    The Musi River is a major river in southern Sumatra, Indonesia, that flows through the city of Palembang and serves as an important transportation and economic lifeline for the region.
  • E. Miljacka River
    The Miljacka River is a small but historically significant river in Bosnia and Herzegovina that flows through the center of Sarajevo, shaping the city's landscape and urban life.
  • 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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc514eb6c8190b3b74a603c717729 completed March 8, 2026, 6:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3df86bc819088db92eecee69fd3 completed March 14, 2026, 2:11 a.m.
Created at: March 8, 2026, 3:26 p.m.