Triple

T10795952
Position Surface form Disambiguated ID Type / Status
Subject Hajino Nakamaro E254705 entity
Predicate hasGivenName P17 FINISHED
Object Nakamaro
Nakamaro is a Japanese given name historically associated with figures such as the Nara-period court noble and poet Ōtomo no Yakamochi’s contemporary, Fujiwara no Nakamaro.
 E885551 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: Nakamaro | Statement: [Hajino Nakamaro, hasGivenName, Nakamaro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nakamaro
Context triple: [Hajino Nakamaro, hasGivenName, Nakamaro]
  • A. Marape
    Marape is the surname of James Marape, the Prime Minister of Papua New Guinea.
  • B. Makato
    Makato is a coastal municipality in the province of Aklan in the Western Visayas region of the Philippines.
  • C. Mamburao
    Mamburao is a coastal municipality in the Philippines that serves as the capital of the province of Occidental Mindoro in the Mimaropa region.
  • D. Nabaloi
    Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
  • E. Yanaon
    Yanaon is the former name of Yanam, a small coastal town in India that was once part of French India and retains a distinct Franco-Indian cultural heritage.
  • 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: Nakamaro
Triple: [Hajino Nakamaro, hasGivenName, Nakamaro]
Generated description
Nakamaro is a Japanese given name historically associated with figures such as the Nara-period court noble and poet Ōtomo no Yakamochi’s contemporary, Fujiwara no Nakamaro.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nakamaro
Target entity description: Nakamaro is a Japanese given name historically associated with figures such as the Nara-period court noble and poet Ōtomo no Yakamochi’s contemporary, Fujiwara no Nakamaro.
  • A. Marape
    Marape is the surname of James Marape, the Prime Minister of Papua New Guinea.
  • B. Makato
    Makato is a coastal municipality in the province of Aklan in the Western Visayas region of the Philippines.
  • C. Mamburao
    Mamburao is a coastal municipality in the Philippines that serves as the capital of the province of Occidental Mindoro in the Mimaropa region.
  • D. Nabaloi
    Nabaloi is an Austronesian language spoken by the Ibaloi people of the northern Philippines, particularly in the Benguet region of Luzon.
  • E. Yanaon
    Yanaon is the former name of Yanam, a small coastal town in India that was once part of French India and retains a distinct Franco-Indian cultural heritage.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73332dbfc8190904434846957b618 completed April 9, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69de5654e2c48190a8f078b8164707e2 completed April 14, 2026, 2:59 p.m.
NEDg Description generation batch_69de5eae7ab88190a0c512cfe61e3458 completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de60907e1081908405b6d71adbd388 completed April 14, 2026, 3:43 p.m.
Created at: April 8, 2026, 9:17 p.m.