Triple

T2740732
Position Surface form Disambiguated ID Type / Status
Subject Imo State E60742 entity
Predicate hasLocalGovernmentArea P8215 FINISHED
Object Njaba
Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
 E295911 NE FINISHED

How this triple was built (4 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: Njaba | Statement: [Imo State, hasLocalGovernmentArea, Njaba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Njaba
Context triple: [Imo State, hasLocalGovernmentArea, Njaba]
  • A. Nansio
    Nansio is the main town and administrative center of Ukerewe Island in Lake Victoria, Tanzania.
  • B. Nembe
    Nembe is an Ijaw subgroup and town in Bayelsa State, Nigeria, known historically as a coastal trading center in the Niger Delta.
  • C. Njuká
    Njuká is an alternative name for the Ndyuka language, a creole spoken primarily by the Ndyuka Maroon community in Suriname and French Guiana.
  • D. Ndzebi
    Ndzebi is a Bantu language spoken primarily by the Nzebi people of Gabon and neighboring regions.
  • E. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Njaba
Triple: [Imo State, hasLocalGovernmentArea, Njaba]
Generated description
Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Njaba
Target entity description: Njaba is a local government area in southeastern Nigeria known for its communities within Imo State and its role in local administration and commerce.
  • A. Nansio
    Nansio is the main town and administrative center of Ukerewe Island in Lake Victoria, Tanzania.
  • B. Nembe
    Nembe is an Ijaw subgroup and town in Bayelsa State, Nigeria, known historically as a coastal trading center in the Niger Delta.
  • C. Njuká
    Njuká is an alternative name for the Ndyuka language, a creole spoken primarily by the Ndyuka Maroon community in Suriname and French Guiana.
  • D. Ndzebi
    Ndzebi is a Bantu language spoken primarily by the Nzebi people of Gabon and neighboring regions.
  • E. Ndowe
    Ndowe is a Bantu language spoken by the Ndowe people along the coastal region of Equatorial Guinea.
  • F. None of above. chosen

Provenance (5 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_69ab4b77febc819095603eb012cd141b completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdb2f210881909126307cc92ebfef completed March 7, 2026, 8 a.m.
NED1 Entity disambiguation (via context triple) batch_69afbbca8ac081909ce86d4cd911b4f1 completed March 10, 2026, 6:35 a.m.
NEDg Description generation batch_69afbcc1dd988190826ab05e55adf1ee completed March 10, 2026, 6:40 a.m.
NED2 Entity disambiguation (via description) batch_69afbd452e1c8190a3ee9eaf642e80a0 completed March 10, 2026, 6:42 a.m.
Created at: March 6, 2026, 9:56 p.m.