Triple

T11168197
Position Surface form Disambiguated ID Type / Status
Subject Myene E264207 entity
Predicate hasDialect P4251 FINISHED
Object Orungu
Orungu is a dialect of the Myene language spoken by the Orungu people of coastal Gabon.
 E908750 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: Orungu | Statement: [Myene, hasDialect, Orungu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Orungu
Context triple: [Myene, hasDialect, Orungu]
  • A. Itilima
    Itilima is a town and administrative district in northern Tanzania's Simiyu Region, known primarily for its role in local governance and agriculture.
  • B. 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.
  • C. Kunda
    Kunda is a small industrial town in northern Estonia known for its cement industry and archaeological significance.
  • D. Ndugu
    Ndugu is a surname of likely African origin borne by various individuals, including those with the given name Bailey.
  • E. Ngundu
    Ngundu is a small settlement in southern Zimbabwe that serves as a roadside stop and trading center along major routes between Harare and Beitbridge.
  • 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: Orungu
Triple: [Myene, hasDialect, Orungu]
Generated description
Orungu is a dialect of the Myene language spoken by the Orungu people of coastal Gabon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Orungu
Target entity description: Orungu is a dialect of the Myene language spoken by the Orungu people of coastal Gabon.
  • A. Itilima
    Itilima is a town and administrative district in northern Tanzania's Simiyu Region, known primarily for its role in local governance and agriculture.
  • B. 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.
  • C. Kunda
    Kunda is a small industrial town in northern Estonia known for its cement industry and archaeological significance.
  • D. Ndugu
    Ndugu is a surname of likely African origin borne by various individuals, including those with the given name Bailey.
  • E. Ngundu
    Ngundu is a small settlement in southern Zimbabwe that serves as a roadside stop and trading center along major routes between Harare and Beitbridge.
  • 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_69d6aa9dafac8190bd90d2c74f661aa7 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e88843cc81909e503f0921c6d297 completed April 9, 2026, 5:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69e463945e40819087c6bdbc322a6d54 completed April 19, 2026, 5:09 a.m.
NEDg Description generation batch_69e46c37efec81908aa709587c37569d completed April 19, 2026, 5:46 a.m.
NED2 Entity disambiguation (via description) batch_69e47292cdd08190b05c4c8b09f4f918 completed April 19, 2026, 6:13 a.m.
Created at: April 8, 2026, 9:29 p.m.