Triple

T9301656
Position Surface form Disambiguated ID Type / Status
Subject Heald Green railway station E223776 entity
Predicate stationCode P1289 FINISHED
Object HDG
HDG is the National Rail station code for Heald Green railway station in Greater Manchester, England.
 E789496 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: HDG | Statement: [Heald Green railway station, stationCode, HDG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HDG
Context triple: [Heald Green railway station, stationCode, HDG]
  • A. Hdn
    Hdn is the station code for Handen station, a commuter rail stop in the Stockholm County region of Sweden.
  • B. HdM
    HdM is the commonly used abbreviation for Stuttgart Media University, a German university specializing in media, information, and communication studies.
  • C. HDX
    HDX is an open humanitarian data platform that enables organizations to share, find, and use data for crisis preparedness and response.
  • D. DHM
    DHM is the commonly used abbreviation for the German Historical Museum in Berlin, a major institution dedicated to documenting and presenting German history.
  • E. DGP
    DGP is the highest-ranking police officer in an Indian state or union territory, responsible for overseeing the entire state police force.
  • 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: HDG
Triple: [Heald Green railway station, stationCode, HDG]
Generated description
HDG is the National Rail station code for Heald Green railway station in Greater Manchester, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HDG
Target entity description: HDG is the National Rail station code for Heald Green railway station in Greater Manchester, England.
  • A. Hdn
    Hdn is the station code for Handen station, a commuter rail stop in the Stockholm County region of Sweden.
  • B. HdM
    HdM is the commonly used abbreviation for Stuttgart Media University, a German university specializing in media, information, and communication studies.
  • C. HDX
    HDX is an open humanitarian data platform that enables organizations to share, find, and use data for crisis preparedness and response.
  • D. DHM
    DHM is the commonly used abbreviation for the German Historical Museum in Berlin, a major institution dedicated to documenting and presenting German history.
  • E. DGP
    DGP is the highest-ranking police officer in an Indian state or union territory, responsible for overseeing the entire state police force.
  • 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_69ca8424d0f08190831e2e93c6533aeb completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd08d1d954819098be177addafa406 completed April 1, 2026, noon
NED1 Entity disambiguation (via context triple) batch_69d0b26302608190a59f3ed0694ce6d9 completed April 4, 2026, 6:40 a.m.
NEDg Description generation batch_69d0b3234d088190a8ed13b4d4772fb5 completed April 4, 2026, 6:43 a.m.
NED2 Entity disambiguation (via description) batch_69d0b3bcd5548190ba1af3d0fa72780a completed April 4, 2026, 6:46 a.m.
Created at: March 30, 2026, 7:36 p.m.