Triple

T17526093
Position Surface form Disambiguated ID Type / Status
Subject Jerusalem Windows E426798 entity
Predicate hasPart P35 FINISHED
Object Gad window NE NERFINISHED

How this triple was built (2 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: Gad window | Statement: [Jerusalem Windows, hasPart, Gad window]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gad window
Context triple: [Jerusalem Windows, hasPart, Gad window]
  • A. Gad 2
    Gad 2 is a ski lift at Snowbird Ski and Summer Resort, providing access to terrain on the mountain.
  • B. Gad chosen
    Gad is a biblical figure, one of the twelve sons of Jacob and the founder of the Israelite tribe that bears his name.
  • C. Gui da gui
    Gui da gui is a 1980 Hong Kong horror-comedy film, internationally known as "Encounters of the Spooky Kind," that blends martial arts with supernatural elements and is often credited with popularizing the jiangshi (hopping vampire) genre.
  • D. Gadzoom
    Gadzoom is a high-speed chairlift at Snowbird Ski and Summer Resort in Utah, serving popular intermediate and advanced terrain.
  • E. GDK
    GDK is the low-level drawing and windowing system library that underpins GTK, providing an abstraction layer over the underlying graphical system.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889de677081909b22d2657b1f0292 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e452d6a2548190acf26f2d5d4aab66 completed April 19, 2026, 3:58 a.m.
Created at: April 10, 2026, 5:49 a.m.