Triple

T4429422
Position Surface form Disambiguated ID Type / Status
Subject Province of Cebu E95287 entity
Predicate contains P35 FINISHED
Object Kawasan Falls E228706 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: Kawasan Falls | Statement: [Province of Cebu, contains, Kawasan Falls]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kawasan Falls
Context triple: [Province of Cebu, contains, Kawasan Falls]
  • A. Kawasan Falls chosen
    Kawasan Falls is a popular multi-tiered waterfall and swimming spot in the Philippines known for its turquoise waters, lush jungle surroundings, and canyoneering adventures.
  • B. Kempty Falls
    Kempty Falls is a popular cascading waterfall and picnic spot near Mussoorie in the Indian state of Uttarakhand, known for its scenic beauty and cool mountain surroundings.
  • C. Tanda Falls
    Tanda Falls is a scenic waterfall and popular natural getaway located near Mirzapur in Uttar Pradesh, India.
  • D. Nachi Falls
    Nachi Falls is one of Japan’s tallest and most famous waterfalls, revered as a sacred site and scenic highlight near the Kumano Nachi Taisha shrine in Wakayama Prefecture.
  • E. Furepe Falls
    Furepe Falls is a scenic coastal waterfall in Japan’s Shiretoko Peninsula, known for its dramatic drop from seaside cliffs directly into the Sea of Okhotsk and its rich surrounding wildlife.
  • 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_69b3453c2a0c8190926b574c90766db9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35568767c819084d5e18b56a4745e completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6136caa248190a84423cede1908c3 completed March 15, 2026, 2:03 a.m.
Created at: March 12, 2026, 11:30 p.m.