Triple

T8911242
Position Surface form Disambiguated ID Type / Status
Subject Greenhithe for Bluewater E212186 entity
Predicate stationCode P1289 FINISHED
Object GNH
GNH is the National Rail station code for Greenhithe for Bluewater railway station in Kent, England.
 E765700 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: GNH | Statement: [Greenhithe for Bluewater, stationCode, GNH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GNH
Context triple: [Greenhithe for Bluewater, stationCode, GNH]
  • A. GNH
    GNH is an alternative development philosophy and measurement framework from Bhutan that prioritizes holistic well-being and sustainable happiness over purely economic growth.
  • B. Gongjin
    Gongjin is the courtesy name of Zhou Yu, a renowned Eastern Han dynasty military general and strategist best known for his role in the Battle of Red Cliffs.
  • C. Ghindae
    Ghindae is a town in Eritrea located within the Northern Red Sea administrative region.
  • D. KGH
    KGH is the National Rail station code for Kinghorn railway station in Fife, Scotland.
  • E. Aegukga
    Aegukga is the national anthem of South Korea, expressing patriotic devotion and love for the country.
  • 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: GNH
Triple: [Greenhithe for Bluewater, stationCode, GNH]
Generated description
GNH is the National Rail station code for Greenhithe for Bluewater railway station in Kent, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GNH
Target entity description: GNH is the National Rail station code for Greenhithe for Bluewater railway station in Kent, England.
  • A. GNH
    GNH is an alternative development philosophy and measurement framework from Bhutan that prioritizes holistic well-being and sustainable happiness over purely economic growth.
  • B. Gongjin
    Gongjin is the courtesy name of Zhou Yu, a renowned Eastern Han dynasty military general and strategist best known for his role in the Battle of Red Cliffs.
  • C. Ghindae
    Ghindae is a town in Eritrea located within the Northern Red Sea administrative region.
  • D. KGH
    KGH is the National Rail station code for Kinghorn railway station in Fife, Scotland.
  • E. Aegukga
    Aegukga is the national anthem of South Korea, expressing patriotic devotion and love for the country.
  • 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_69ca8393b1808190bd4336787ffa2c40 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6523b9348190a7cefac9e73e2004 completed April 1, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfba3c92c481909589e6a3c9469136 completed April 3, 2026, 1:01 p.m.
NEDg Description generation batch_69cfbabf33a08190a18d13b9078c00e2 completed April 3, 2026, 1:03 p.m.
NED2 Entity disambiguation (via description) batch_69cfbba71a948190afc03a1df9e5777c completed April 3, 2026, 1:07 p.m.
Created at: March 30, 2026, 6:55 p.m.