Triple

T11006043
Position Surface form Disambiguated ID Type / Status
Subject Te Rauparaha E260120 entity
Predicate spouse P13 FINISHED
Object Marore
Marore was the wife of the renowned Ngāti Toa chief and war leader Te Rauparaha in early 19th-century Aotearoa New Zealand.
 E897909 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: Marore | Statement: [Te Rauparaha, spouse, Marore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marore
Context triple: [Te Rauparaha, spouse, Marore]
  • A. Zułów
    Zułów is a village in present-day Lithuania best known as the birthplace of Polish statesman and military leader Józef Piłsudski.
  • B. Savo
    Savo is a historical and cultural region in eastern Finland known for its lakes, forests, and distinctive Savonian dialect and traditions.
  • C. Savo
    Savo is a town in Kenya’s Central Province known as one of the region’s notable settlements.
  • D. Riva
    Riva is a coastal neighborhood and popular recreational area on the Asian side of Istanbul, known for its beaches, river, and natural scenery.
  • E. Tuscania
    Tuscania is a historic town in Italy’s Lazio region, known for its well-preserved medieval architecture and Etruscan archaeological sites.
  • 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: Marore
Triple: [Te Rauparaha, spouse, Marore]
Generated description
Marore was the wife of the renowned Ngāti Toa chief and war leader Te Rauparaha in early 19th-century Aotearoa New Zealand.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marore
Target entity description: Marore was the wife of the renowned Ngāti Toa chief and war leader Te Rauparaha in early 19th-century Aotearoa New Zealand.
  • A. Zułów
    Zułów is a village in present-day Lithuania best known as the birthplace of Polish statesman and military leader Józef Piłsudski.
  • B. Savo
    Savo is a town in Kenya’s Central Province known as one of the region’s notable settlements.
  • C. Savo
    Savo is a historical and cultural region in eastern Finland known for its lakes, forests, and distinctive Savonian dialect and traditions.
  • D. Riva
    Riva is a coastal neighborhood and popular recreational area on the Asian side of Istanbul, known for its beaches, river, and natural scenery.
  • E. Tuscania
    Tuscania is a historic town in Italy’s Lazio region, known for its well-preserved medieval architecture and Etruscan archaeological sites.
  • 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_69d6aa8a6a548190a750f944ccdc8064 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d79756e6bc81908eae9d5f8ff0d43f completed April 9, 2026, 12:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3454cb6008190b24b128d507f2cf4 completed April 18, 2026, 8:48 a.m.
NEDg Description generation batch_69e35570b0bc8190a939b0c8e3ce8105 completed April 18, 2026, 9:57 a.m.
NED2 Entity disambiguation (via description) batch_69e359563fec8190b432b35b8502c3f4 completed April 18, 2026, 10:13 a.m.
Created at: April 8, 2026, 9:25 p.m.