Triple

T13920793
Position Surface form Disambiguated ID Type / Status
Subject Gunnersbury station E334735 entity
Predicate railcode P27071 FINISHED
Object GUN
GUN is the National Rail station code for Gunnersbury railway station in London, United Kingdom.
E1069644 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: GUN | Statement: [Gunnersbury station, railcode, GUN]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: GUN
Context triple: [Gunnersbury station, railcode, GUN]
  • A. Gun
    "Gun" is a heavy, riff-driven rock track by Soundgarden from their 1989 album *Louder Than Love*.
  • B. Gun
    Gun is a Scottish surname most prominently linked to Clan Gunn, a historic Highland clan from Caithness and Sutherland.
  • C. Guns
    "Guns" is a song by the indie rock supergroup Nice As Fuck, known for its minimalist style and politically charged themes.
  • D. Table Gun
    Table Gun is a Philippe Starck–designed table lamp shaped like a firearm, created as part of the provocative Gun Lamp series for the Italian lighting brand Flos.
  • E. Life gun
    A Life gun is a pattern in Conway’s Game of Life that periodically generates an endless stream of moving configurations called gliders.
  • 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: GUN
Triple: [Gunnersbury station, railcode, GUN]
Generated description
GUN is the National Rail station code for Gunnersbury railway station in London, United Kingdom.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: GUN
Target entity description: GUN is the National Rail station code for Gunnersbury railway station in London, United Kingdom.
  • A. Gun
    "Gun" is a heavy, riff-driven rock track by Soundgarden from their 1989 album *Louder Than Love*.
  • B. Gun
    Gun is a Scottish surname most prominently linked to Clan Gunn, a historic Highland clan from Caithness and Sutherland.
  • C. Guns
    "Guns" is a song by the indie rock supergroup Nice As Fuck, known for its minimalist style and politically charged themes.
  • D. Table Gun
    Table Gun is a Philippe Starck–designed table lamp shaped like a firearm, created as part of the provocative Gun Lamp series for the Italian lighting brand Flos.
  • E. Life gun
    A Life gun is a pattern in Conway’s Game of Life that periodically generates an endless stream of moving configurations called gliders.
  • 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_69d81c5f739081908bc05b2461f54828 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2aa428ac819084e7c4b244d15f20 completed April 14, 2026, 11:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7ce7c4a788190a1e7619a00ab0c2e completed May 3, 2026, 10:38 p.m.
NEDg Description generation batch_69f9fd5b82f48190b0b89ddca25883cc completed May 5, 2026, 2:23 p.m.
NED2 Entity disambiguation (via description) batch_69f9fea0a9dc8190b5b65dfec9626949 completed May 5, 2026, 2:28 p.m.
Created at: April 9, 2026, 10:16 p.m.