Triple

T23531488
Position Surface form Disambiguated ID Type / Status
Subject Hounslow railway station E576582 entity
Predicate stationCode P1289 FINISHED
Object HOU
HOU is the three-letter National Rail station code for Hounslow railway station in London, England.
 E1592126 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: HOU | Statement: [Hounslow railway station, stationCode, HOU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HOU
Context triple: [Hounslow railway station, stationCode, HOU]
  • A. HOU
    HOU is the commonly used acronym for the Hellenic Open University, a Greek institution specializing in distance and lifelong learning.
  • B. Houston
    Houston is a major U.S. metropolis known for its energy industry, NASA’s Johnson Space Center, and its diverse, rapidly growing population.
  • C. Houston
    Houston is a village in Renfrewshire, Scotland, known for its historic conservation area and role as a commuter settlement near Glasgow.
  • D. Hou
    Hou is a Chinese surname and given name that can represent various historical figures, modern individuals, and fictional characters depending on context.
  • E. Huston
    Huston is a surname most famously associated with a prominent American film family that includes acclaimed director John Huston and actress Anjelica Huston.
  • 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: HOU
Triple: [Hounslow railway station, stationCode, HOU]
Generated description
HOU is the three-letter National Rail station code for Hounslow railway station in London, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HOU
Target entity description: HOU is the three-letter National Rail station code for Hounslow railway station in London, England.
  • A. HOU
    HOU is the commonly used acronym for the Hellenic Open University, a Greek institution specializing in distance and lifelong learning.
  • B. Houston
    Houston is a major U.S. metropolis known for its energy industry, NASA’s Johnson Space Center, and its diverse, rapidly growing population.
  • C. Houston
    Houston is a village in Renfrewshire, Scotland, known for its historic conservation area and role as a commuter settlement near Glasgow.
  • D. Hou
    Hou is a Chinese surname and given name that can represent various historical figures, modern individuals, and fictional characters depending on context.
  • E. Huston
    Huston is a surname most famously associated with a prominent American film family that includes acclaimed director John Huston and actress Anjelica Huston.
  • 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_69e245f5a8848190a2ba42e271c6c31f completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ac78581c8190bd9d09ce2be8029d completed April 29, 2026, 7 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0cdf559a988190926f6f2ae298da58 completed May 19, 2026, 10:08 p.m.
NEDg Description generation batch_6a0d7213f9508190a8884846e19079e3 completed May 20, 2026, 8:34 a.m.
NED2 Entity disambiguation (via description) batch_6a0d72ad1b148190bbe5f65e84ac2837 completed May 20, 2026, 8:37 a.m.
Created at: April 17, 2026, 6:09 p.m.