Triple

T9857366
Position Surface form Disambiguated ID Type / Status
Subject Expressway S17 E239620 entity
Predicate abbreviation P43 FINISHED
Object S17
S17 is a Polish expressway forming part of the national road network, connecting Warsaw with the eastern regions of Poland.
 E825704 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: S17 | Statement: [Expressway S17, abbreviation, S17]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: S17
Context triple: [Expressway S17, abbreviation, S17]
  • A. S9
    S9 is a line of the Berlin S-Bahn rapid transit network that connects Berlin Brandenburg Airport with central and western parts of the city.
  • B. S9
    S9 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting multiple cities across the area.
  • C. S11
    S11 is a commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving regional passenger traffic across the metropolitan area.
  • D. S1
    S1 is a key commuter rail line of the Berlin S-Bahn network, connecting central Berlin with its northern and southwestern suburbs.
  • E. S1
    S1 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting key cities and suburbs in the area.
  • 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: S17
Triple: [Expressway S17, abbreviation, S17]
Generated description
S17 is a Polish expressway forming part of the national road network, connecting Warsaw with the eastern regions of Poland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: S17
Target entity description: S17 is a Polish expressway forming part of the national road network, connecting Warsaw with the eastern regions of Poland.
  • A. S9
    S9 is a line of the Berlin S-Bahn rapid transit network that connects Berlin Brandenburg Airport with central and western parts of the city.
  • B. S9
    S9 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting multiple cities across the area.
  • C. S11
    S11 is a commuter rail line within Germany’s Rhine-Ruhr S-Bahn network, serving regional passenger traffic across the metropolitan area.
  • D. S1
    S1 is a key commuter rail line of the Berlin S-Bahn network, connecting central Berlin with its northern and southwestern suburbs.
  • E. S1
    S1 is a regional S-Bahn rail line within Germany’s Rhine-Ruhr metropolitan transit network, connecting key cities and suburbs in the area.
  • 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_69ca84e6493081909cf58c8d42ea856b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb39864188190a2d8c0ee911f00c2 completed April 2, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1e43b2de881909e00f6701d1c7b54 completed April 5, 2026, 4:25 a.m.
NEDg Description generation batch_69d1e5204f748190b1f56ee5469828a2 completed April 5, 2026, 4:29 a.m.
NED2 Entity disambiguation (via description) batch_69d1e598243481909278cb3c911ce3db completed April 5, 2026, 4:31 a.m.
Created at: March 30, 2026, 8:35 p.m.