Triple

T2826524
Position Surface form Disambiguated ID Type / Status
Subject Mano River Union E54935 entity
Predicate headquartersLocation P62 FINISHED
Object Freetown E70581 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: Freetown | Statement: [Mano River Union, headquartersLocation, Freetown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Freetown
Context triple: [Mano River Union, headquartersLocation, Freetown]
  • A. Freetown chosen
    Freetown is the capital and largest city of Sierra Leone, known as a historic port and former center for resettled freed slaves in West Africa.
  • B. Freetown
    Freetown is a historic rural town in Bristol County, southeastern Massachusetts, known for its forests, ponds, and the reputedly haunted Freetown-Fall River State Forest.
  • C. Monrovia
    Monrovia is the largest city and main economic and administrative center of Liberia, located on the Atlantic coast in West Africa.
  • D. Banjul
    Banjul is the capital and principal port city of The Gambia, located on an island at the mouth of the Gambia River in West Africa.
  • E. Serekunda
    Serekunda is the most populous urban center and a major commercial hub in The Gambia.
  • 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_69ab49e100c0819082a40cb797383243 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abde94ba848190b2c990936e07e6bb completed March 7, 2026, 8:15 a.m.
NED1 Entity disambiguation (via context triple) batch_69afceb20c508190ba87e102ba250a00 completed March 10, 2026, 7:56 a.m.
Created at: March 6, 2026, 9:59 p.m.