Triple

T7840831
Position Surface form Disambiguated ID Type / Status
Subject Western Oceanic E181797 entity
Predicate hasLanguage P15 FINISHED
Object Mangseng
Mangseng is an Oceanic language spoken in parts of western Melanesia, belonging to the Western Oceanic branch of the Austronesian language family.
 E696166 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: Mangseng | Statement: [Western Oceanic, hasLanguage, Mangseng]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mangseng
Context triple: [Western Oceanic, hasLanguage, Mangseng]
  • A. Malango
    Malango is an Oceanic language spoken in the Solomon Islands, closely related to and geographically adjacent to the Ghari language.
  • B. Sawanih
    Sawanih is a notable literary work by the Indian poet Faizi, recognized for its contribution to classical Persian literature in South Asia.
  • C. Mahinog
    Mahinog is a coastal municipality on Camiguin Island in the Philippines known for its rural communities and access to nearby islets and marine attractions.
  • D. Mawé
    Mawé is an indigenous Tupian language spoken by the Sateré-Mawé people of the Brazilian Amazon.
  • E. Marangona
    Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
  • 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: Mangseng
Triple: [Western Oceanic, hasLanguage, Mangseng]
Generated description
Mangseng is an Oceanic language spoken in parts of western Melanesia, belonging to the Western Oceanic branch of the Austronesian language family.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mangseng
Target entity description: Mangseng is an Oceanic language spoken in parts of western Melanesia, belonging to the Western Oceanic branch of the Austronesian language family.
  • A. Malango
    Malango is an Oceanic language spoken in the Solomon Islands, closely related to and geographically adjacent to the Ghari language.
  • B. Sawanih
    Sawanih is a notable literary work by the Indian poet Faizi, recognized for its contribution to classical Persian literature in South Asia.
  • C. Mahinog
    Mahinog is a coastal municipality on Camiguin Island in the Philippines known for its rural communities and access to nearby islets and marine attractions.
  • D. Mawé
    Mawé is an indigenous Tupian language spoken by the Sateré-Mawé people of the Brazilian Amazon.
  • E. Marangona
    Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
  • 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_69ca8285d6488190a95d4c02d7354b53 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb14c589748190b34d0911d373e194 completed March 31, 2026, 12:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69cb5aca5e348190bb73fc4748093248 completed March 31, 2026, 5:25 a.m.
NEDg Description generation batch_69cb5def38e88190864d84abd7959aa3 completed March 31, 2026, 5:38 a.m.
NED2 Entity disambiguation (via description) batch_69cb765db28881909ac34071ec6889b3 completed March 31, 2026, 7:23 a.m.
Created at: March 30, 2026, 4:47 p.m.