Triple

T5592991
Position Surface form Disambiguated ID Type / Status
Subject Mussau-Emira E146925 entity
Predicate hasAlternativeName P39 FINISHED
Object Mussau
Mussau is an island in Papua New Guinea’s Bismarck Archipelago, known for its distinct Oceanic languages and rich Melanesian-Polynesian cultural heritage.
 E529778 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: Mussau | Statement: [Mussau-Emira, hasAlternativeName, Mussau]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mussau
Context triple: [Mussau-Emira, hasAlternativeName, Mussau]
  • A. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • B. Lomonosovo
    Lomonosovo is a rural locality in Russia’s Arkhangelsk Oblast, best known as the birthplace of the polymath Mikhail Lomonosov.
  • C. Kholmogory
    Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
  • D. Malaya Nevka
    Malaya Nevka is a distributary channel of the Neva River in Saint Petersburg, Russia, forming part of the city’s intricate river and canal network.
  • E. Nagatinskaya
    Nagatinskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the Nagatinsky Zaton area of southern Moscow.
  • 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: Mussau
Triple: [Mussau-Emira, hasAlternativeName, Mussau]
Generated description
Mussau is an island in Papua New Guinea’s Bismarck Archipelago, known for its distinct Oceanic languages and rich Melanesian-Polynesian cultural heritage.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mussau
Target entity description: Mussau is an island in Papua New Guinea’s Bismarck Archipelago, known for its distinct Oceanic languages and rich Melanesian-Polynesian cultural heritage.
  • A. Vorontsovskaya
    Vorontsovskaya is a metro station on Moscow’s Big Circle Line serving the southwestern part of the city.
  • B. Lomonosovo
    Lomonosovo is a rural locality in Russia’s Arkhangelsk Oblast, best known as the birthplace of the polymath Mikhail Lomonosov.
  • C. Kholmogory
    Kholmogory is a historic Russian town in the Arkhangelsk region that served as an important early northern trading and administrative center.
  • D. Malaya Nevka
    Malaya Nevka is a distributary channel of the Neva River in Saint Petersburg, Russia, forming part of the city’s intricate river and canal network.
  • E. Nagatinskaya
    Nagatinskaya is a Moscow Metro station serving the Serpukhovsko–Timiryazevskaya Line in the Nagatinsky Zaton area of southern Moscow.
  • 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_69c009036c408190981a8d690b679b67 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c020bb08648190ab1f66cc3e897e6d completed March 22, 2026, 5:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0286b4d2c8190a3224f3082316dc8 completed March 22, 2026, 5:35 p.m.
NEDg Description generation batch_69c0372e86c08190bf586256cab23d22 completed March 22, 2026, 6:38 p.m.
NED2 Entity disambiguation (via description) batch_69c038e7df488190a960266045c4f41f completed March 22, 2026, 6:46 p.m.
Created at: March 22, 2026, 3:38 p.m.