Triple

T13565743
Position Surface form Disambiguated ID Type / Status
Subject Jonglei E324029 entity
Predicate bordersWith P224 FINISHED
Object Unity State E793157 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: Unity State | Statement: [Jonglei, bordersWith, Unity State]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Unity State
Context triple: [Jonglei, bordersWith, Unity State]
  • A. Unity State chosen
    Unity State is an oil-rich region in northern South Sudan that became a major battleground and humanitarian crisis zone during the South Sudanese Civil War.
  • B. ConcreteState
    ConcreteState is a specific implementation of the State interface in the State design pattern that encapsulates behavior associated with a particular state of a context object.
  • C. FSM
    FSM is the three-letter ISO 3166-1 alpha-3 country code for the Federated States of Micronesia, a Pacific island nation.
  • D. FSM
    FSM is the abbreviation for the French Submarine Forces, the branch of the French Navy responsible for operating and maintaining France’s submarine fleet, including its nuclear deterrent.
  • E. State Loop
    State Loop is a type of short, state-maintained highway that typically connects major routes or provides a bypass around urban areas within a U.S. state highway system.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb00cecd48190a9a2caff3d424817 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75daf1bfc8190bf22eb9ef242f54f completed May 3, 2026, 2:37 p.m.
Created at: April 9, 2026, 9:48 p.m.