Triple

T8761207
Position Surface form Disambiguated ID Type / Status
Subject Asakusa Station E208201 entity
Predicate hasStationCode P1289 FINISHED
Object A-18
A-18 is the station code assigned to Asakusa Station on Tokyo’s Toei Asakusa Line.
E755104 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: A-18 | Statement: [Asakusa Station, hasStationCode, A-18]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: A-18
Context triple: [Asakusa Station, hasStationCode, A-18]
  • A. AC-8
    AC-8 was a class of Southern Pacific Railroad articulated steam locomotives in the distinctive cab-forward configuration, used primarily for heavy freight service over mountainous routes in the early 20th century.
  • B. LC-18A
    LC-18A is a launch complex at Cape Canaveral used historically for early U.S. rocket launches, including the Vanguard program.
  • C. A86
    A86 is a major orbital motorway forming part of the ring road system around Paris, France.
  • D. CP-140 Aurora
    The CP-140 Aurora is a Canadian long-range maritime patrol and anti-submarine warfare aircraft based on the Lockheed P-3 Orion airframe and used primarily for surveillance and reconnaissance missions.
  • E. A1A
    A1A is a scenic coastal highway in Florida that runs along the Atlantic Ocean, known for connecting popular beaches and tourist destinations.
  • 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: A-18
Triple: [Asakusa Station, hasStationCode, A-18]
Generated description
A-18 is the station code assigned to Asakusa Station on Tokyo’s Toei Asakusa Line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: A-18
Target entity description: A-18 is the station code assigned to Asakusa Station on Tokyo’s Toei Asakusa Line.
  • A. AC-8
    AC-8 was a class of Southern Pacific Railroad articulated steam locomotives in the distinctive cab-forward configuration, used primarily for heavy freight service over mountainous routes in the early 20th century.
  • B. LC-18A
    LC-18A is a launch complex at Cape Canaveral used historically for early U.S. rocket launches, including the Vanguard program.
  • C. A86
    A86 is a major orbital motorway forming part of the ring road system around Paris, France.
  • D. CP-140 Aurora
    The CP-140 Aurora is a Canadian long-range maritime patrol and anti-submarine warfare aircraft based on the Lockheed P-3 Orion airframe and used primarily for surveillance and reconnaissance missions.
  • E. A1A
    A1A is a scenic coastal highway in Florida that runs along the Atlantic Ocean, known for connecting popular beaches and tourist destinations.
  • 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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5dfa9d6c81908c4c6b3a6f84f67d completed March 31, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf4354a4c081908c338db408694abf completed April 3, 2026, 4:34 a.m.
NEDg Description generation batch_69cf44b3ce2c8190b109189990ae6564 completed April 3, 2026, 4:40 a.m.
NED2 Entity disambiguation (via description) batch_69cf4578473081909fc55632c366a56a completed April 3, 2026, 4:43 a.m.
Created at: March 30, 2026, 6:40 p.m.