Triple

T16264122
Position Surface form Disambiguated ID Type / Status
Subject Ségur station E394829 entity
Predicate hasStationCode P1289 FINISHED
Object SÉG
SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
 E1204196 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: SÉG | Statement: [Ségur station, hasStationCode, SÉG]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SÉG
Context triple: [Ségur station, hasStationCode, SÉG]
  • A. SEGU
    SEGU is the ICAO airport code for José Joaquín de Olmedo International Airport, the main air gateway serving Guayaquil, Ecuador.
  • B. Seg-El
    Seg-El is the protagonist of the TV series "Krypton," a young Kryptonian and grandfather of Superman who fights to restore his family's honor and save his planet's future.
  • C. SEK
    SEK is the official currency code for the Swedish krona, the national currency of Sweden.
  • D. SEGOT
    SEGOT is the UN/LOCODE identifier for the Port of Gothenburg, Sweden’s largest seaport and a major logistics hub in Northern Europe.
  • E. Sek
    Sek is the Vulcan son of Star Trek: Voyager’s tactical officer Tuvok.
  • 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: SÉG
Triple: [Ségur station, hasStationCode, SÉG]
Generated description
SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SÉG
Target entity description: SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
  • A. SEGU
    SEGU is the ICAO airport code for José Joaquín de Olmedo International Airport, the main air gateway serving Guayaquil, Ecuador.
  • B. Seg-El
    Seg-El is the protagonist of the TV series "Krypton," a young Kryptonian and grandfather of Superman who fights to restore his family's honor and save his planet's future.
  • C. SEK
    SEK is the official currency code for the Swedish krona, the national currency of Sweden.
  • D. SEGOT
    SEGOT is the UN/LOCODE identifier for the Port of Gothenburg, Sweden’s largest seaport and a major logistics hub in Northern Europe.
  • E. Sek
    Sek is the Vulcan son of Star Trek: Voyager’s tactical officer Tuvok.
  • 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_69d87f221d8081909b0b2063e7528ba2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e245c672248190a4261be4696d52c5 completed April 17, 2026, 2:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0017b5f3a8819083128cf2b90cfd84 completed May 10, 2026, 5:29 a.m.
NEDg Description generation batch_6a001978fed48190963b327da30c31f0 completed May 10, 2026, 5:36 a.m.
NED2 Entity disambiguation (via description) batch_6a001a0def548190a1d800f858f3cb02 completed May 10, 2026, 5:39 a.m.
Created at: April 10, 2026, 5:04 a.m.