Triple

T802059
Position Surface form Disambiguated ID Type / Status
Subject Griffith Park E17149 entity
Predicate hasAttraction P105 FINISHED
Object Mount Lee E27606 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: Mount Lee | Statement: [Griffith Park, hasAttraction, Mount Lee]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Lee
Context triple: [Griffith Park, hasAttraction, Mount Lee]
  • A. Mount Lee chosen
    Mount Lee is a hill in the Hollywood Hills of Los Angeles best known as the site overlooking the iconic Hollywood Sign.
  • B. Mount Tennent
    Mount Tennent is a prominent mountain in the Australian Capital Territory known for its popular hiking trails and panoramic views within the Namadgi National Park.
  • C. Mount Catherine
    Mount Catherine is the highest mountain in Egypt, located in the southern Sinai Peninsula and known for its rugged terrain and religious significance.
  • D. Mount Ainslie
    Mount Ainslie is a prominent hill in Canberra, Australia, known for its popular lookout offering panoramic views over the city and its surrounding landscape.
  • E. Elephant Mountain
    Elephant Mountain is a popular hiking spot in Taipei known for its short trail and panoramic views of the city skyline and Taipei 101.
  • 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aa9e0f0081909d2a89387d6c08e1 completed March 1, 2026, 9:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69a7cf4f602481908f9c399063a605b9 completed March 4, 2026, 6:21 a.m.
Created at: March 1, 2026, 7:38 p.m.