Triple

T14868603
Position Surface form Disambiguated ID Type / Status
Subject Stadelhofen railway station E349680 entity
Predicate hasStationCode P1289 FINISHED
Object ZLSH
ZLSH is the station code used to identify Zürich Stadelhofen railway station in Switzerland’s rail network.
 E1124418 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: ZLSH | Statement: [Stadelhofen railway station, hasStationCode, ZLSH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ZLSH
Context triple: [Stadelhofen railway station, hasStationCode, ZLSH]
  • A. ZLS
    ZLS is the IATA airport code assigned to a specific airfield or airport associated with the location abbreviated as LST.
  • B. ZL
    ZL is the IATA airline designator used by Rex Airlines, a regional carrier based in Australia.
  • C. ZL
    ZL is the official station code used to identify Zwolle railway station in the Netherlands’ rail network.
  • D. ZLW
    ZLW is the National Rail station code assigned to Whitechapel railway station in London.
  • E. ZHSY
    ZHSY is the ICAO airport code assigned to Shiyan Wudangshan Airport in Hubei Province, China.
  • 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: ZLSH
Triple: [Stadelhofen railway station, hasStationCode, ZLSH]
Generated description
ZLSH is the station code used to identify Zürich Stadelhofen railway station in Switzerland’s rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ZLSH
Target entity description: ZLSH is the station code used to identify Zürich Stadelhofen railway station in Switzerland’s rail network.
  • A. ZLS
    ZLS is the IATA airport code assigned to a specific airfield or airport associated with the location abbreviated as LST.
  • B. ZL
    ZL is the IATA airline designator used by Rex Airlines, a regional carrier based in Australia.
  • C. ZL
    ZL is the official station code used to identify Zwolle railway station in the Netherlands’ rail network.
  • D. ZLW
    ZLW is the National Rail station code assigned to Whitechapel railway station in London.
  • E. ZHSY
    ZHSY is the ICAO airport code assigned to Shiyan Wudangshan Airport in Hubei Province, China.
  • 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_69d822ee4f408190b6ac3b2fa434f0df completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded5776b848190bfe3a06ff261dc31 completed April 15, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe651067cc8190b9c218ef1f802762 completed May 8, 2026, 10:34 p.m.
NEDg Description generation batch_69fe675dd7288190901df5f7806f9b3f completed May 8, 2026, 10:44 p.m.
NED2 Entity disambiguation (via description) batch_69fe67f2fab881908b8be1aa344ee5b5 completed May 8, 2026, 10:47 p.m.
Created at: April 10, 2026, 1:55 a.m.