Triple

T11851449
Position Surface form Disambiguated ID Type / Status
Subject Amber E281917 entity
Predicate hasLandmark P105 FINISHED
Object Maota Lake E297724 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: Maota Lake | Statement: [Amber, hasLandmark, Maota Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maota Lake
Context triple: [Amber, hasLandmark, Maota Lake]
  • A. Maota Lake chosen
    Maota Lake is a historic artificial lake in Jaipur, India, known for its scenic setting below the Amber Fort and its role as a former water source for the fort complex.
  • B. Majang Lake
    Majang Lake is a scenic reservoir and leisure destination in Paju, South Korea, known for its walking trails, lakeside cafes, and tranquil natural surroundings.
  • C. Haflong Lake
    Haflong Lake is a scenic natural lake in Assam, India, known as a popular spot for boating, birdwatching, and leisure tourism in the hill town of Haflong.
  • D. Miage Lake
    Miage Lake is a proglacial lake in the Italian Alps formed at the terminus of the Miage Glacier, known for its striking setting beneath Mont Blanc.
  • E. Kankaria Lake
    Kankaria Lake is a historic, man-made lake in Ahmedabad, India, known for its recreational facilities, zoo, and popular waterfront promenade.
  • 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_69d6ab287ba48190a5178779fd19b9b7 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a65db52c8190a218736da17d0153 completed April 10, 2026, 7:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe8bba60c8819087b614cea03eb078 completed May 9, 2026, 1:19 a.m.
Created at: April 8, 2026, 9:43 p.m.