Triple

T9745170
Position Surface form Disambiguated ID Type / Status
Subject Region 10 E236287 entity
Predicate hasHighestPoint P210 FINISHED
Object Mount Dulang-dulang E817864 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 Dulang-dulang | Statement: [Region 10, hasHighestPoint, Mount Dulang-dulang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Dulang-dulang
Context triple: [Region 10, hasHighestPoint, Mount Dulang-dulang]
  • A. Mount Dulang-dulang chosen
    Mount Dulang-dulang is one of the highest and most biodiverse peaks in the Philippines, located in the northern part of Mindanao.
  • B. Mount Welirang
    Mount Welirang is an active stratovolcano in East Java, Indonesia, known for its sulfur mining and frequent fumarolic activity.
  • C. Mount Nanlaud
    Mount Nanlaud is the tallest mountain on the Micronesian island of Pohnpei, known for its lush tropical rainforest and frequent cloud cover.
  • D. Mount Pangasun
    Mount Pangasun is the tallest volcanic peak in the remote Babuyan Islands of the northern Philippines.
  • E. Godangbong Peak
    Godangbong Peak is the main summit of Geumjeongsan, offering panoramic views and popular hiking routes near Busan, South Korea.
  • 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_69ca84d3e24481908a476e2231123cf9 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9f2f8e648190ad94c940f9dc1de0 completed April 1, 2026, 10:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1bcd2e08c8190808b58fdabe0c9d3 completed April 5, 2026, 1:37 a.m.
Created at: March 30, 2026, 8:23 p.m.