Triple

T7432422
Position Surface form Disambiguated ID Type / Status
Subject York city walls E171524 entity
Predicate hasPart P35 FINISHED
Object Tower Forty-one
Tower Forty-one is one of the defensive towers incorporated into the historic medieval city walls of York, England.
 E667158 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 Forty-one | Statement: [York city walls, hasPart, Tower Forty-one]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tower Forty-one
Context triple: [York city walls, hasPart, Tower Forty-one]
  • A. Tower Forty
    Tower Forty is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • B. Tower Thirty-nine
    Tower Thirty-nine is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • C. Tower One Hundred
    Tower One Hundred is a defensive medieval tower incorporated into the historic York city walls in York, England.
  • D. Pan Peninsula East Tower
    Pan Peninsula East Tower is a prominent residential skyscraper in London’s Docklands, forming one half of the twin-tower Pan Peninsula development near Canary Wharf.
  • E. Landmark Tower
    Landmark Tower is a prominent skyscraper in Yokohama, Japan, known for its height, observation deck, and role as a major commercial and office complex.
  • 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 Forty-one
Triple: [York city walls, hasPart, Tower Forty-one]
Generated description
Tower Forty-one is one of the defensive towers incorporated into the historic medieval city walls of York, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tower Forty-one
Target entity description: Tower Forty-one is one of the defensive towers incorporated into the historic medieval city walls of York, England.
  • A. Tower Forty
    Tower Forty is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • B. Tower Thirty-nine
    Tower Thirty-nine is one of the numbered defensive towers incorporated into the historic medieval city walls of York, England.
  • C. Tower One Hundred
    Tower One Hundred is a defensive medieval tower incorporated into the historic York city walls in York, England.
  • D. Pan Peninsula East Tower
    Pan Peninsula East Tower is a prominent residential skyscraper in London’s Docklands, forming one half of the twin-tower Pan Peninsula development near Canary Wharf.
  • E. Landmark Tower
    Landmark Tower is a prominent skyscraper in Yokohama, Japan, known for its height, observation deck, and role as a major commercial and office complex.
  • 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_69c68a63491881909281f73d4d5643bf completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f325ea908190b668fd4ce646f1e6 completed March 27, 2026, 9:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69c83449b84c81909167f29e901c0881 completed March 28, 2026, 8:04 p.m.
NEDg Description generation batch_69c835ce5bbc8190b968535c16cfc660 completed March 28, 2026, 8:10 p.m.
NED2 Entity disambiguation (via description) batch_69c836a80eb081908b9937944fe18661 completed March 28, 2026, 8:14 p.m.
Created at: March 27, 2026, 3:12 p.m.