Triple

T2642366
Position Surface form Disambiguated ID Type / Status
Subject Loulé railway station E62899 entity
Predicate railwayStationCode P1289 FINISHED
Object LLE
LLE is the station code for Loulé railway station in Portugal’s Algarve region.
 E285803 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: LLE | Statement: [Loulé railway station, railwayStationCode, LLE]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LLE
Context triple: [Loulé railway station, railwayStationCode, LLE]
  • A. LEM
    LEM is the original abbreviation for the Apollo Lunar Module, the spacecraft used by NASA astronauts to land on and ascend from the Moon during the Apollo missions.
  • B. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • C. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • D. LCC
    LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
  • E. LEU
    LEU is the National Rail station code for Leuchars (for St Andrews) railway station in Fife, Scotland.
  • 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: LLE
Triple: [Loulé railway station, railwayStationCode, LLE]
Generated description
LLE is the station code for Loulé railway station in Portugal’s Algarve region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LLE
Target entity description: LLE is the station code for Loulé railway station in Portugal’s Algarve region.
  • A. LEM
    LEM is the original abbreviation for the Apollo Lunar Module, the spacecraft used by NASA astronauts to land on and ascend from the Moon during the Apollo missions.
  • B. Le
    Le is a common Vietnamese surname shared by many notable figures in the country’s history and culture.
  • C. LAL
    LAL is the standard NBA abbreviation for the Los Angeles Lakers basketball franchise.
  • D. LCC
    LCC is a comprehensive library classification system developed by the Library of Congress to organize and arrange books and other materials by subject.
  • E. LEU
    LEU is the National Rail station code for Leuchars (for St Andrews) railway station in Fife, Scotland.
  • 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_69ab4c3f2dcc819082df80f5e032f690 completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abd8ff34988190ba9d69ce9d77c71d completed March 7, 2026, 7:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69af98bfd4008190a30675ebaf01e483 completed March 10, 2026, 4:06 a.m.
NEDg Description generation batch_69af99416924819099d4acb1a2d60e0c completed March 10, 2026, 4:08 a.m.
NED2 Entity disambiguation (via description) batch_69af99adadb08190a44f2286b25bf0aa completed March 10, 2026, 4:10 a.m.
Created at: March 6, 2026, 9:53 p.m.