Triple

T36002596
Position Surface form Disambiguated ID Type / Status
Subject Meitetsu Bus E1041172 entity
Predicate usesTicketingSystem P1740 FINISHED
Object Manaca IC card
The Manaca IC card is a rechargeable contactless smart card used for public transportation and electronic payments in the Nagoya metropolitan area of Japan.
E2165071 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: Manaca IC card | Statement: [Meitetsu Bus, usesTicketingSystem, Manaca IC card]
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: Manaca IC card
Triple: [Meitetsu Bus, usesTicketingSystem, Manaca IC card]
Generated description
The Manaca IC card is a rechargeable contactless smart card used for public transportation and electronic payments in the Nagoya metropolitan area of Japan.

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_69f76e2a02208190aedd1f9025a8b300 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7ac8454b081909bb6c21740d4eb6f completed May 3, 2026, 8:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38bff3d3688190b5dca82c12d426be completed June 22, 2026, 4:54 a.m.
NEDg Description generation batch_6a38c0a8a0908190a845f3f6e7040e1e completed June 22, 2026, 4:57 a.m.
NED2 Entity disambiguation (via description) batch_6a38c164f0e88190bef255d462f21732 completed June 22, 2026, 5 a.m.
Created at: May 3, 2026, 4:07 p.m.