Triple

T10670975
Position Surface form Disambiguated ID Type / Status
Subject Frankfurt skyline E251483 entity
Predicate hasPart P35 FINISHED
Object Tower 185
Tower 185 is a prominent high-rise office building in Frankfurt am Main, Germany, known for its distinctive architecture and role in shaping the city’s modern financial district skyline.
E879572 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: Tower 185 | Statement: [Frankfurt skyline, hasPart, Tower 185]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tower 185
Context triple: [Frankfurt skyline, hasPart, Tower 185]
  • A. Tower Fifty-eight
    Tower Fifty-eight is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • B. Tower Fifty-nine
    Tower Fifty-nine is one of the defensive towers incorporated into the historic medieval city walls of York, England.
  • C. Tower Fifty-one
    Tower Fifty-one is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • D. Tower Seventy-six
    Tower Seventy-six is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • E. Tower Fifty-four
    Tower Fifty-four is one of the defensive towers incorporated into the historic medieval city walls of York, England.
  • 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: Tower 185
Triple: [Frankfurt skyline, hasPart, Tower 185]
Generated description
Tower 185 is a prominent high-rise office building in Frankfurt am Main, Germany, known for its distinctive architecture and role in shaping the city’s modern financial district skyline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tower 185
Target entity description: Tower 185 is a prominent high-rise office building in Frankfurt am Main, Germany, known for its distinctive architecture and role in shaping the city’s modern financial district skyline.
  • A. Tower Fifty-eight
    Tower Fifty-eight is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • B. Tower Fifty-nine
    Tower Fifty-nine is one of the defensive towers incorporated into the historic medieval city walls of York, England.
  • C. Tower Fifty-one
    Tower Fifty-one is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • D. Tower Seventy-six
    Tower Seventy-six is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • E. Tower Fifty-four
    Tower Fifty-four is one of the defensive towers incorporated into the historic medieval city walls of York, England.
  • 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_69d6aa5b0d2881909584b20efc5877f0 completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6f86390648190851693aedce6b7ad completed April 9, 2026, 12:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69d98865f700819093c8cadc6fcef75f completed April 10, 2026, 11:31 p.m.
NEDg Description generation batch_69d98ae8403c81908a229aa06bd0388a completed April 10, 2026, 11:42 p.m.
NED2 Entity disambiguation (via description) batch_69d98ce9ba0c8190a7c62fa670e23705 completed April 10, 2026, 11:51 p.m.
Created at: April 8, 2026, 9:09 p.m.