Triple

T24322794
Position Surface form Disambiguated ID Type / Status
Subject Sekigahara E613013 entity
Predicate hasRoadsideStation P107291 FINISHED
Object Michi-no-Eki Sekigahara
Michi-no-Eki Sekigahara is a Japanese roadside rest area and local tourism hub near the historic Sekigahara battlefield, offering traveler services, regional products, and historical information.
 E1627069 NE FINISHED

How this triple was built (3 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: Michi-no-Eki Sekigahara | Statement: [Sekigahara, hasRoadsideStation, Michi-no-Eki Sekigahara]
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: Michi-no-Eki Sekigahara
Triple: [Sekigahara, hasRoadsideStation, Michi-no-Eki Sekigahara]
Generated description
Michi-no-Eki Sekigahara is a Japanese roadside rest area and local tourism hub near the historic Sekigahara battlefield, offering traveler services, regional products, and historical information.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasRoadsideStation
Context triple: [Sekigahara, hasRoadsideStation, Michi-no-Eki Sekigahara]
  • A. hasRoadsideFacility chosen
    Indicates that a location or route segment is associated with a facility or service situated along its roadside.
  • B. hasServiceStationNetworkIn
    Indicates that an entity operates or maintains a network of service stations within a specified geographic area or region.
  • C. hasStationNear
    Indicates that one entity has a station located in close proximity to another entity.
  • D. hasStationAt
    Indicates that an entity maintains or operates a station located at a specified place.
  • E. hasPumpingStation
    Indicates that one entity possesses, contains, or is served by a pumping station associated with it.
  • F. None of above.

Provenance (6 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_69e2d7da491c8190b6e6218af50923db completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f292ad4cc881908794b501cf70b7a1 completed April 29, 2026, 11:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc9e4a1748190b5637b682458124a completed May 22, 2026, 3:13 a.m.
NEDg Description generation batch_6a0fcade9db88190b79f8f03c9b5f51f completed May 22, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcb724a888190838a30e05e556421 completed May 22, 2026, 3:20 a.m.
PD Predicate disambiguation batch_69f1c45f45888190a9ccc225906c34bd completed April 29, 2026, 8:42 a.m.
Created at: April 18, 2026, 1:52 a.m.