Triple

T11133988
Position Surface form Disambiguated ID Type / Status
Subject Luga River E263361 entity
Predicate hasCityOnRiver P17819 FINISHED
Object Kingisepp E197494 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: Kingisepp | Statement: [Luga River, hasCityOnRiver, Kingisepp]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kingisepp
Context triple: [Luga River, hasCityOnRiver, Kingisepp]
  • A. Kingisepp chosen
    Kingisepp is a town in northwestern Russia near the Estonian border, known for its industrial base and historical roots dating back to the 14th century.
  • B. Muroran
    Muroran is an industrial port city in southern Hokkaido, Japan, known for its steel industry and scenic coastal landscapes.
  • C. Zikhron Ya’akov
    Zikhron Ya’akov is a historic town in northern Israel known for its early Zionist agricultural settlement, wineries, and scenic location overlooking the Mediterranean.
  • D. Lichtenrade
    Lichtenrade is a southern residential locality of Berlin known for its village-like character, green spaces, and proximity to the city’s outskirts.
  • E. Podolsk
    Podolsk is a major industrial city and former center of machine-building located just south of Moscow in western Russia.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8347a248190837e8c26f25f553a completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e441f00d7c8190a8fe8e0c1169e6b0 completed April 19, 2026, 2:46 a.m.
Created at: April 8, 2026, 9:28 p.m.