Triple

T12291815
Position Surface form Disambiguated ID Type / Status
Subject Shanghai Metro Line 18 E292981 entity
Predicate hasStation P35 FINISHED
Object Hangtou station
Hangtou station is a metro station in Shanghai, China, serving passengers on the city’s Line 18.
E973956 NE FINISHED

How this triple was built (4 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: Hangtou station | Statement: [Shanghai Metro Line 18, hasStation, Hangtou station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hangtou station
Context triple: [Shanghai Metro Line 18, hasStation, Hangtou station]
  • A. Nanpu station
    Nanpu station is a metro station in Guangzhou, China, serving passengers on the city’s Line 2 rapid transit route.
  • B. Xinzhuang Station
    Xinzhuang Station is a major Shanghai Metro interchange station in Minhang District, serving as a key southern transport hub in the city’s network.
  • C. Tuqiao Station
    Tuqiao Station is a subway station on Beijing's Batong Line serving the eastern suburbs of the city.
  • D. Dongshankou Station
    Dongshankou Station is an underground interchange station on the Guangzhou Metro system serving the Dongshan area of Guangzhou, China.
  • E. Jinyintan Station
    Jinyintan Station is a metro station in Wuhan, China, serving passengers on the city's Line 2 rapid transit route.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Hangtou station
Triple: [Shanghai Metro Line 18, hasStation, Hangtou station]
Generated description
Hangtou station is a metro station in Shanghai, China, serving passengers on the city’s Line 18.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hangtou station
Target entity description: Hangtou station is a metro station in Shanghai, China, serving passengers on the city’s Line 18.
  • A. Nanpu station
    Nanpu station is a metro station in Guangzhou, China, serving passengers on the city’s Line 2 rapid transit route.
  • B. Xinzhuang Station
    Xinzhuang Station is a major Shanghai Metro interchange station in Minhang District, serving as a key southern transport hub in the city’s network.
  • C. Tuqiao Station
    Tuqiao Station is a subway station on Beijing's Batong Line serving the eastern suburbs of the city.
  • D. Dongshankou Station
    Dongshankou Station is an underground interchange station on the Guangzhou Metro system serving the Dongshan area of Guangzhou, China.
  • E. Jinyintan Station
    Jinyintan Station is a metro station in Wuhan, China, serving passengers on the city's Line 2 rapid transit route.
  • F. None of above. chosen

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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91d22ba488190914342fa7e69e159 completed April 10, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e775dac819099d44b61cbccc109 completed May 2, 2026, 3:55 p.m.
NEDg Description generation batch_69f61f5cc5608190a67a888eb5136ada completed May 2, 2026, 3:59 p.m.
NED2 Entity disambiguation (via description) batch_69f62006afcc8190b8e3b55a5fd8eaca completed May 2, 2026, 4:02 p.m.
Created at: April 8, 2026, 9:52 p.m.