Triple

T16397207
Position Surface form Disambiguated ID Type / Status
Subject Palauig E398212 entity
Predicate hasHighestPoint P210 FINISHED
Object Mount Tapulao E315867 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 Tapulao | Statement: [Palauig, hasHighestPoint, Mount Tapulao]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Tapulao
Context triple: [Palauig, hasHighestPoint, Mount Tapulao]
  • A. Mount Tapulao chosen
    Mount Tapulao is a prominent mountain in the Philippines known for its cool climate, pine forests, and challenging hiking trails.
  • B. Mount Arayat
    Mount Arayat is a prominent inactive stratovolcano and pilgrimage site rising from the plains of Pampanga in Central Luzon, Philippines.
  • C. Mount Buko
    Mount Buko is a prominent mountain in Japan’s Saitama Prefecture, known for its limestone quarrying and scenic hiking trails overlooking the Chichibu region.
  • D. Mount Sibayak
    Mount Sibayak is an active stratovolcano in North Sumatra, Indonesia, known for its accessible crater, geothermal vents, and popular hiking trails near the town of Berastagi.
  • E. Mount Nanlaud
    Mount Nanlaud is the tallest mountain on the Micronesian island of Pohnpei, known for its lush tropical rainforest and frequent cloud cover.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e327cb3c708190b64341cb1410ed81 completed April 18, 2026, 6:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004579d9a88190b353952c5c301e9f completed May 10, 2026, 8:44 a.m.
Created at: April 10, 2026, 5:09 a.m.