Triple

T18145356
Position Surface form Disambiguated ID Type / Status
Subject DPDgroup E434374 entity
Predicate brand P1500 FINISHED
Object SEUR
SEUR is a Spanish express parcel and logistics company operating under the international DPDgroup network.
 E1307420 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: SEUR | Statement: [DPDgroup, brand, SEUR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SEUR
Context triple: [DPDgroup, brand, SEUR]
  • A. SEUSL
    SEUSL is a public university in Sri Lanka’s Eastern Province known for providing higher education and research opportunities across a range of disciplines.
  • B. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • C. SÉG
    SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
  • D. SEBE
    SEBE is the commonly used acronym for the Faculty of Science, Engineering and Built Environment at Deakin University.
  • E. SEGU
    SEGU is the ICAO airport code for José Joaquín de Olmedo International Airport, the main air gateway serving Guayaquil, Ecuador.
  • 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: SEUR
Triple: [DPDgroup, brand, SEUR]
Generated description
SEUR is a Spanish express parcel and logistics company operating under the international DPDgroup network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SEUR
Target entity description: SEUR is a Spanish express parcel and logistics company operating under the international DPDgroup network.
  • A. SEUSL
    SEUSL is a public university in Sri Lanka’s Eastern Province known for providing higher education and research opportunities across a range of disciplines.
  • B. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • C. SÉG
    SÉG is the station code for Ségur, a Paris Métro station on Line 10 in the 15th arrondissement of Paris, France.
  • D. SEBE
    SEBE is the commonly used acronym for the Faculty of Science, Engineering and Built Environment at Deakin University.
  • E. SEGU
    SEGU is the ICAO airport code for José Joaquín de Olmedo International Airport, the main air gateway serving Guayaquil, Ecuador.
  • 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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de33921c8190b6f645ca63fd146b completed April 19, 2026, 1:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a038554608c819080abf60da5f48a67 completed May 12, 2026, 7:53 p.m.
NEDg Description generation batch_6a03864b84608190b204b08351f1176b completed May 12, 2026, 7:58 p.m.
NED2 Entity disambiguation (via description) batch_6a0386bb53b88190b5cc7e747a9da903 completed May 12, 2026, 7:59 p.m.
Created at: April 10, 2026, 10:29 a.m.