Triple

T7432414
Position Surface form Disambiguated ID Type / Status
Subject York city walls E171524 entity
Predicate hasPart P35 FINISHED
Object Red Tower
Red Tower is a historic defensive tower incorporated into the medieval city walls of York, England.
E664281 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: Red Tower | Statement: [York city walls, hasPart, Red Tower]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Red Tower
Context triple: [York city walls, hasPart, Red Tower]
  • A. Red Tower
    Red Tower is a historic medieval tower and landmark in the German city of Chemnitz.
  • B. Tower of Glass
    Tower of Glass is a 1970 science fiction novel by Robert Silverberg that explores themes of artificial intelligence, class hierarchy, and the ethics of creating sentient beings.
  • C. City of Glass
    City of Glass is a postmodern detective novel by Paul Auster that blends mystery, metafiction, and philosophical inquiry into identity and language.
  • D. White Tower
    The White Tower is a prominent Renaissance-era bell tower and landmark in the historic center of Hradec Králové in the Czech Republic.
  • E. White Tower
    The White Tower is a historic neo-Gothic tower and former imperial leisure pavilion located within the palace-and-park ensemble of Tsarskoye Selo near St. Petersburg, Russia.
  • 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: Red Tower
Triple: [York city walls, hasPart, Red Tower]
Generated description
Red Tower is a historic defensive tower incorporated into the medieval city walls of York, England.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Red Tower
Target entity description: Red Tower is a historic defensive tower incorporated into the medieval city walls of York, England.
  • A. Red Tower
    Red Tower is a historic medieval tower and landmark in the German city of Chemnitz.
  • B. Tower of Glass
    Tower of Glass is a 1970 science fiction novel by Robert Silverberg that explores themes of artificial intelligence, class hierarchy, and the ethics of creating sentient beings.
  • C. City of Glass
    City of Glass is a postmodern detective novel by Paul Auster that blends mystery, metafiction, and philosophical inquiry into identity and language.
  • D. White Tower
    The White Tower is a prominent Renaissance-era bell tower and landmark in the historic center of Hradec Králové in the Czech Republic.
  • E. White Tower
    The White Tower is a historic neo-Gothic tower and former imperial leisure pavilion located within the palace-and-park ensemble of Tsarskoye Selo near St. Petersburg, Russia.
  • 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_69c81f187f5081909d171835278c035c completed March 28, 2026, 6:34 p.m.
NEDg Description generation batch_69c8230a58008190ad10d012f4070435 completed March 28, 2026, 6:50 p.m.
NED2 Entity disambiguation (via description) batch_69c823ec05288190aa3c0b812ce1662f completed March 28, 2026, 6:54 p.m.
Created at: March 27, 2026, 3:12 p.m.