Triple

T28813264
Position Surface form Disambiguated ID Type / Status
Subject 富山市 E727572 entity
Predicate 鉄道路線 P848 FINISHED
Object 富山ライトレール(富山地方鉄道富山港線)
富山ライトレール(富山地方鉄道富山港線)は、富山市中心部と富山港エリアを結び、LRT(次世代型路面電車)導入で全国的に注目された都市型鉄道路線である。
E1833493 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: 富山ライトレール(富山地方鉄道富山港線) | Statement: [富山市, 鉄道路線, 富山ライトレール(富山地方鉄道富山港線)]
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: 富山ライトレール(富山地方鉄道富山港線)
Triple: [富山市, 鉄道路線, 富山ライトレール(富山地方鉄道富山港線)]
Generated description
富山ライトレール(富山地方鉄道富山港線)は、富山市中心部と富山港エリアを結び、LRT(次世代型路面電車)導入で全国的に注目された都市型鉄道路線である。

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_69f0319c38948190bca746ad60fd25ba completed April 28, 2026, 4:03 a.m.
NER Named-entity recognition batch_69f658f163a88190b1dd222eaa0f93ea completed May 2, 2026, 8:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a24a28238988190815a8a5c3fc15fea completed June 6, 2026, 10:43 p.m.
NEDg Description generation batch_6a24a650b8408190abe70dc1108b8368 completed June 6, 2026, 10:59 p.m.
NED2 Entity disambiguation (via description) batch_6a24aa401b2c8190bf774922baa12667 completed June 6, 2026, 11:16 p.m.
Created at: April 28, 2026, 6:31 a.m.