Triple

T12959408
Position Surface form Disambiguated ID Type / Status
Subject Tours station E310098 entity
Predicate hasIataCode P2569 FINISHED
Object XSH
XSH is the IATA airport code for the railway station in Tours, France, used for air-rail intermodal ticketing.
 E1013115 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: XSH | Statement: [Tours station, hasIataCode, XSH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: XSH
Context triple: [Tours station, hasIataCode, XSH]
  • A. XSHG
    XSHG is the ISO 10383 market identifier code (MIC) assigned to the Shanghai Stock Exchange, one of the largest stock exchanges in the world.
  • B. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • C. XHP
    XHP is a PHP extension for Facebook's Hack language that lets developers write XML-like syntax directly in code to create robust, type-safe user interface components.
  • D. XHP
    XHP is the IATA station code assigned to Paris's Gare de l'Est railway station.
  • E. XSC
    XSC is the IATA airport code for South Caicos Airport in the Turks and Caicos Islands.
  • 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: XSH
Triple: [Tours station, hasIataCode, XSH]
Generated description
XSH is the IATA airport code for the railway station in Tours, France, used for air-rail intermodal ticketing.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: XSH
Target entity description: XSH is the IATA airport code for the railway station in Tours, France, used for air-rail intermodal ticketing.
  • A. XSHG
    XSHG is the ISO 10383 market identifier code (MIC) assigned to the Shanghai Stock Exchange, one of the largest stock exchanges in the world.
  • B. XU
    XU was a clandestine Norwegian intelligence organization that gathered and transmitted vital information to the Allies during the German occupation in World War II.
  • C. XHP
    XHP is the IATA station code assigned to Paris's Gare de l'Est railway station.
  • D. XHP
    XHP is a PHP extension for Facebook's Hack language that lets developers write XML-like syntax directly in code to create robust, type-safe user interface components.
  • E. XSC
    XSC is the IATA airport code for South Caicos Airport in the Turks and Caicos Islands.
  • 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_69d7bdfb57a88190836b743e2825feca completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d97e2e44908190bb8b43fc5c3b8a8a completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6b8e006cc819091e5f4b044cadea4 completed May 3, 2026, 2:54 a.m.
NEDg Description generation batch_69f6b9dac2c88190850304023f156969 completed May 3, 2026, 2:58 a.m.
NED2 Entity disambiguation (via description) batch_69f6bb337b708190a874cec01d588236 completed May 3, 2026, 3:04 a.m.
Created at: April 9, 2026, 5:44 p.m.