Triple

T14247896
Position Surface form Disambiguated ID Type / Status
Subject Vilankulo E353181 entity
Predicate roadConnection P385 FINISHED
Object Inhambane E136410 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: Inhambane | Statement: [Vilankulo, roadConnection, Inhambane]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Inhambane
Context triple: [Vilankulo, roadConnection, Inhambane]
  • A. Inhambane Province chosen
    Inhambane Province is a coastal region in southern Mozambique known for its historic towns, coconut palms, and popular beach and diving destinations along the Indian Ocean.
  • B. Nampula
    Nampula is a major city in northern Mozambique that serves as an important commercial and transportation hub for the region.
  • C. Atambua
    Atambua is a town in East Nusa Tenggara, Indonesia, located near the border with Timor-Leste and serving as an important regional trade and transit center.
  • D. Tete Province
    Tete Province is a region in northwestern Mozambique known for its significant hydroelectric resources, including the Cahora Bassa Dam on the Zambezi River.
  • E. Mbeya
    Mbeya is a major city in southwestern Tanzania, serving as a commercial and transport hub near the Zambian border.
  • 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_69d8278c43e08190824146f4632b89a5 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6295ef9081909cfb0c1283bca21a completed April 14, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd46794e9c819093312a2c304e554e completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:08 a.m.