Triple

T32169519
Position Surface form Disambiguated ID Type / Status
Subject JR黄檗駅 E821669 entity
Predicate adjacentStationOnNaraLine P181682 FINISHED
Object 宇治駅
宇治駅は、京都府宇治市に位置し、JR奈良線が乗り入れる宇治観光の玄関口となっている鉄道駅です。
 E1995225 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: 宇治駅 | Statement: [JR黄檗駅, adjacentStationOnNaraLine, 宇治駅]
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: 宇治駅
Triple: [JR黄檗駅, adjacentStationOnNaraLine, 宇治駅]
Generated description
宇治駅は、京都府宇治市に位置し、JR奈良線が乗り入れる宇治観光の玄関口となっている鉄道駅です。
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: adjacentStationOnNaraLine
Context triple: [JR黄檗駅, adjacentStationOnNaraLine, 宇治駅]
  • A. adjacentStationOnNambuLine
    Indicates that one station is directly next to another station along the Nambu railway line, with no other stations in between.
  • B. adjacentStationOnKarasumaLine
    Indicates that one station is directly next to another station along the Karasuma railway line.
  • C. adjacentStationOnNambokuLine
    Indicates that one station is directly next to another station along the Namboku railway line.
  • D. adjacentStationOnJRKyotoLine
    Indicates that one station is directly next to another station along the JR Kyoto railway line, with no other stations in between.
  • E. adjacentStationOnOsakaLoopLine
    Indicates that one station is directly next to another station along the Osaka Loop railway line, with no other stations in between.
  • F. None of above. chosen

Provenance (7 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_69f3490699a48190bbef96b198e8fade completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f7805ce6208190ac6dbd9c97989978 completed May 3, 2026, 5:05 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2f0bd90ffc819083310e0650e4e1f9 completed June 14, 2026, 8:15 p.m.
NEDg Description generation batch_6a2f15db9f1c8190852475cbdbafdd67 completed June 14, 2026, 8:58 p.m.
NED2 Entity disambiguation (via description) batch_6a2f16e68f588190b18717146305a932 completed June 14, 2026, 9:02 p.m.
PD Predicate disambiguation batch_69f77956ec648190ba4fb7e9d83fd107 completed May 3, 2026, 4:35 p.m.
PDg Predicate description generation batch_69f7805c25dc8190b9977c561ba15975 completed May 3, 2026, 5:05 p.m.
Created at: May 1, 2026, 12:33 a.m.