Triple

T28900897
Position Surface form Disambiguated ID Type / Status
Subject 新竹市 E732946 entity
Predicate hasHighSpeedRailStationNearby P50052 FINISHED
Object 高鐵新竹站
高鐵新竹站是服務新竹地區、連接台灣高鐵南北路線的重要交通樞紐車站。
 E1841048 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: 高鐵新竹站 | Statement: [新竹市, hasHighSpeedRailStationNearby, 高鐵新竹站]
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: 高鐵新竹站
Triple: [新竹市, hasHighSpeedRailStationNearby, 高鐵新竹站]
Generated description
高鐵新竹站是服務新竹地區、連接台灣高鐵南北路線的重要交通樞紐車站。
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasHighSpeedRailStationNearby
Context triple: [新竹市, hasHighSpeedRailStationNearby, 高鐵新竹站]
  • A. hasHighSpeedRailStation chosen
    Indicates that a location is served by a high-speed rail station where high-speed trains regularly stop.
  • B. hasRailStation
    Indicates that one entity possesses, contains, or is served by a rail station.
  • C. hasRailwayStation
    Indicates that a place or location is served by, or contains, a railway station.
  • D. hasRailwayStationOn
    Indicates that a railway station is located on or serves a particular railway line, route, or network segment.
  • E. hasNearbyRailwayStation
    Indicates that a railway station is located within a short or convenient distance from the referenced entity.
  • 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_69f05b08c2008190ac426a035a2ed66d completed April 28, 2026, 7 a.m.
NER Named-entity recognition batch_69fd2a215d6c8190a1a428ccaee603f1 completed May 8, 2026, 12:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a24ec34a9948190a1ee692c79e8ff5d completed June 7, 2026, 3:57 a.m.
NEDg Description generation batch_6a24eeb3c3008190b4ce860d20ed4c67 completed June 7, 2026, 4:08 a.m.
NED2 Entity disambiguation (via description) batch_6a24ef0945d88190939fbcfa77f6131d completed June 7, 2026, 4:09 a.m.
PD Predicate disambiguation batch_69fd28ef19688190bb8370f2812a43e7 completed May 8, 2026, 12:06 a.m.
Created at: April 28, 2026, 8:02 a.m.