Triple

T17992564
Position Surface form Disambiguated ID Type / Status
Subject Madona Municipality E430411 entity
Predicate contains P35 FINISHED
Object Lake Lubāns 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: Lake Lubāns | Statement: [Madona Municipality, contains, Lake Lubāns]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lake Lubāns
Context triple: [Madona Municipality, contains, Lake Lubāns]
  • A. Lake Lubāns chosen
    Lake Lubāns is the largest lake in Latvia, known for its extensive wetlands and importance as a habitat for migratory birds.
  • B. al-Qusayr Lake
    al-Qusayr Lake is a body of water located within Syria’s Aleppo Governorate, known as a local inland lake in the country’s north.
  • C. Lake Qadisiyah
    Lake Qadisiyah is a large artificial reservoir in western Iraq formed on the Euphrates River, primarily used for hydroelectric power generation, irrigation, and water storage.
  • D. Lake Assad
    Lake Assad is Syria’s largest artificial lake, created on the Euphrates River to provide water storage, irrigation, and hydroelectric power.
  • E. Lake Qaraoun
    Lake Qaraoun is Lebanon’s largest artificial lake, created by damming the Litani River and serving as a key source of irrigation, hydropower, and water storage in the Beqaa Valley.
  • 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_69d8b90364248190a37381adea932f42 completed April 10, 2026, 8:46 a.m.
NER Named-entity recognition batch_69e4b2a0f8588190b6090c7cce60a35f completed April 19, 2026, 10:46 a.m.
Created at: April 10, 2026, 10:23 a.m.