Triple

T16687932
Position Surface form Disambiguated ID Type / Status
Subject Peel River E405513 entity
Predicate hasNearbyTown P3883 FINISHED
Object Manilla E909547 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: Manilla | Statement: [Peel River, hasNearbyTown, Manilla]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manilla
Context triple: [Peel River, hasNearbyTown, Manilla]
  • A. Manilla chosen
    Manilla is a small rural town in the New England region of New South Wales, Australia, known for its agriculture and outdoor recreation activities.
  • B. Manila, Philippine Islands
    Manila, Philippine Islands is the capital and chief city of the Philippines, serving as its historic, political, and economic center.
  • C. Bougainvillea City
    Bougainvillea City is a floral-themed nickname for the Malaysian city of Ipoh, reflecting its abundance of bougainvillea plants and scenic charm.
  • D. Manila
    Manila is the capital city of the Philippines, a historic and densely populated coastal metropolis that has long served as the country’s political, economic, and cultural center.
  • E. Manila
    Manila is the OpenStack shared file system service that provides scalable, API-driven management of networked file shares.
  • 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_69d8838c28748190b3f5967c743940ab completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37ea75df481909a7ebb9b2a9d0afd completed April 18, 2026, 12:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a008a45af7c8190bfe09dd0e0573573 completed May 10, 2026, 1:38 p.m.
Created at: April 10, 2026, 5:19 a.m.