Triple

T8412325
Position Surface form Disambiguated ID Type / Status
Subject Tammy Blanchard E198653 entity
Predicate notableWork P4 FINISHED
Object The Ramen Girl
The Ramen Girl is a 2008 romantic comedy-drama film about an American woman in Tokyo who finds purpose and connection by training under a stern ramen chef.
E732796 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: The Ramen Girl | Statement: [Tammy Blanchard, notableWork, The Ramen Girl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Ramen Girl
Context triple: [Tammy Blanchard, notableWork, The Ramen Girl]
  • A. Sakumono
    Sakumono is a coastal suburban community in the Greater Accra Region of Ghana, known for its residential estates and proximity to the Sakumono Lagoon and beach.
  • B. Ramenki
    Ramenki is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Ramenki District of western Moscow, Russia.
  • C. Yo! Sushi
    Yo! Sushi is a UK-based restaurant chain known for its conveyor-belt served Japanese-inspired dishes, particularly sushi.
  • D. The Noodle Maker
    The Noodle Maker is a satirical novel by Chinese writer Ma Jian that critiques contemporary Chinese society through darkly comic, interwoven stories.
  • E. Ma Kai
    Ma Kai is a Chinese politician who served as a Vice Premier of the State Council and played a key role in the country’s economic and financial policymaking.
  • 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: The Ramen Girl
Triple: [Tammy Blanchard, notableWork, The Ramen Girl]
Generated description
The Ramen Girl is a 2008 romantic comedy-drama film about an American woman in Tokyo who finds purpose and connection by training under a stern ramen chef.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: The Ramen Girl
Target entity description: The Ramen Girl is a 2008 romantic comedy-drama film about an American woman in Tokyo who finds purpose and connection by training under a stern ramen chef.
  • A. Sakumono
    Sakumono is a coastal suburban community in the Greater Accra Region of Ghana, known for its residential estates and proximity to the Sakumono Lagoon and beach.
  • B. Ramenki
    Ramenki is a Moscow Metro station serving the Kalininsko–Solntsevskaya Line in the Ramenki District of western Moscow, Russia.
  • C. Yo! Sushi
    Yo! Sushi is a UK-based restaurant chain known for its conveyor-belt served Japanese-inspired dishes, particularly sushi.
  • D. The Noodle Maker
    The Noodle Maker is a satirical novel by Chinese writer Ma Jian that critiques contemporary Chinese society through darkly comic, interwoven stories.
  • E. Ma Kai
    Ma Kai is a Chinese politician who served as a Vice Premier of the State Council and played a key role in the country’s economic and financial policymaking.
  • 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_69ca831201b481909e137936ef99ff11 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cb83e0341c819080506e696131671e completed March 31, 2026, 8:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69ce0322d1448190aceaf7486c110ff7 completed April 2, 2026, 5:48 a.m.
NEDg Description generation batch_69ce0781859c8190bb92f41c00af459b completed April 2, 2026, 6:06 a.m.
NED2 Entity disambiguation (via description) batch_69ce089d09c08190ba321aed4044a862 completed April 2, 2026, 6:11 a.m.
Created at: March 30, 2026, 6:05 p.m.