Triple

T10670984
Position Surface form Disambiguated ID Type / Status
Subject Frankfurt skyline E251483 entity
Predicate hasPart P35 FINISHED
Object Silberturm
Silberturm is a prominent modernist high-rise office tower in Frankfurt am Main, Germany, and a recognizable feature of the city’s financial district skyline.
E880037 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: Silberturm | Statement: [Frankfurt skyline, hasPart, Silberturm]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Silberturm
Context triple: [Frankfurt skyline, hasPart, Silberturm]
  • A. Reichenturm
    Reichenturm is a historic leaning tower and prominent medieval landmark in the Saxon town of Bautzen, Germany.
  • B. Pulverturm
    Pulverturm is a historic defensive tower that forms part of the medieval Musegg Wall fortifications in Lucerne, Switzerland.
  • C. Opernturm
    Opernturm is a prominent modern high-rise office tower in Frankfurt am Main, Germany, known for its sleek design and contribution to the city’s financial district skyline.
  • D. Roter Turm
    Roter Turm is a historic medieval tower and prominent architectural landmark in the city center of Chemnitz, Germany.
  • E. Roter Turm
    Roter Turm is a historic clock and bell tower in Halle (Saale), Germany, and one of the city’s most recognizable architectural landmarks.
  • 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: Silberturm
Triple: [Frankfurt skyline, hasPart, Silberturm]
Generated description
Silberturm is a prominent modernist high-rise office tower in Frankfurt am Main, Germany, and a recognizable feature of the city’s financial district skyline.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Silberturm
Target entity description: Silberturm is a prominent modernist high-rise office tower in Frankfurt am Main, Germany, and a recognizable feature of the city’s financial district skyline.
  • A. Reichenturm
    Reichenturm is a historic leaning tower and prominent medieval landmark in the Saxon town of Bautzen, Germany.
  • B. Pulverturm
    Pulverturm is a historic defensive tower that forms part of the medieval Musegg Wall fortifications in Lucerne, Switzerland.
  • C. Opernturm
    Opernturm is a prominent modern high-rise office tower in Frankfurt am Main, Germany, known for its sleek design and contribution to the city’s financial district skyline.
  • D. Roter Turm
    Roter Turm is a historic medieval tower and prominent architectural landmark in the city center of Chemnitz, Germany.
  • E. Roter Turm
    Roter Turm is a historic clock and bell tower in Halle (Saale), Germany, and one of the city’s most recognizable architectural landmarks.
  • 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_69d998b77db08190bce5a7ce24dbc085 completed April 11, 2026, 12:41 a.m.
NEDg Description generation batch_69d99e8312188190bec3090f34a7b9b9 completed April 11, 2026, 1:06 a.m.
NED2 Entity disambiguation (via description) batch_69d99f50e0888190b8e7b2547e1526af completed April 11, 2026, 1:09 a.m.
Created at: April 8, 2026, 9:09 p.m.