Triple

T12971540
Position Surface form Disambiguated ID Type / Status
Subject Tanimbar Islands E321408 entity
Predicate hasIsland P970 FINISHED
Object Seira
Seira is one of the islands in Indonesia’s remote Tanimbar archipelago in the Maluku province.
E1014512 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: Seira | Statement: [Tanimbar Islands, hasIsland, Seira]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seira
Context triple: [Tanimbar Islands, hasIsland, Seira]
  • A. Seirah
    Seirah is a biblical location mentioned in the Hebrew Bible as a place of refuge associated with the judge Ehud.
  • B. Sanchica
    Sanchica is the fictional daughter of Sancho Panza in Miguel de Cervantes' novel "Don Quixote."
  • C. Seia
    Seia is a municipality and town in central Portugal known for its proximity to the Serra da Estrela mountains and natural park.
  • D. Shizu
    Shizu is the posthumous temple name by which Emperor Guangwu, the restorer and founding ruler of the Eastern Han dynasty in China, is venerated in ancestral rites.
  • E. Reona
    Reona is the Japanese given name of Nobel Prize–winning physicist Leo Esaki, known for his pioneering work on quantum tunneling and semiconductor devices.
  • 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: Seira
Triple: [Tanimbar Islands, hasIsland, Seira]
Generated description
Seira is one of the islands in Indonesia’s remote Tanimbar archipelago in the Maluku province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Seira
Target entity description: Seira is one of the islands in Indonesia’s remote Tanimbar archipelago in the Maluku province.
  • A. Seirah
    Seirah is a biblical location mentioned in the Hebrew Bible as a place of refuge associated with the judge Ehud.
  • B. Sanchica
    Sanchica is the fictional daughter of Sancho Panza in Miguel de Cervantes' novel "Don Quixote."
  • C. Seia
    Seia is a municipality and town in central Portugal known for its proximity to the Serra da Estrela mountains and natural park.
  • D. Shizu
    Shizu is the posthumous temple name by which Emperor Guangwu, the restorer and founding ruler of the Eastern Han dynasty in China, is venerated in ancestral rites.
  • E. Reona
    Reona is the Japanese given name of Nobel Prize–winning physicist Leo Esaki, known for his pioneering work on quantum tunneling and semiconductor devices.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e418d548190be1c73db76cb3aa8 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8ea91f08190b1daf6d05621acf9 completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6b9a1ca54819085da2ca592bf5219 completed May 3, 2026, 2:57 a.m.
NED2 Entity disambiguation (via description) batch_69f6bb304f7c8190a02aa2c5f71cea89 completed May 3, 2026, 3:04 a.m.
Created at: April 9, 2026, 8:36 p.m.