Triple

T7790095
Position Surface form Disambiguated ID Type / Status
Subject Natsume Sōseki E187353 entity
Predicate notableWork P4 FINISHED
Object Mon E243538 NE FINISHED

How this triple was built (2 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: Mon | Statement: [Natsume Sōseki, notableWork, Mon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mon
Context triple: [Natsume Sōseki, notableWork, Mon]
  • A. Mon
    Mon is a town in the northeastern Indian state of Nagaland, known as the headquarters of Mon district and as a cultural center of the Konyak Naga tribe.
  • B. Mon
    The Mon are one of the oldest ethnic groups in mainland Southeast Asia, historically influential in the spread of Theravada Buddhism and early state formation in what is now Myanmar and Thailand.
  • C. mon chosen
    A mon is a traditional Japanese heraldic emblem used to represent individuals, families, clans, or institutions.
  • D. MON
    MON is the standard abbreviation used for the Montreal Canadiens, the historic National Hockey League team based in Montreal, Quebec.
  • E. MON
    MON is the commonly used abbreviation for Poland’s Ministry of National Defence, the government body responsible for the country’s defense policy and armed forces.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cae7ea13f08190a60c5f1863bce816 completed March 30, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69caf62c8568819090c058b0c55b7865 completed March 30, 2026, 10:16 p.m.
Created at: March 30, 2026, 4:25 p.m.