Triple

T19515028
Position Surface form Disambiguated ID Type / Status
Subject Troy VI E488254 entity
Predicate hasCityWallThickness P136195 FINISHED
Object up to several meters LITERAL FINISHED

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: up to several meters | Statement: [Troy VI, hasCityWallThickness, up to several meters]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCityWallThickness
Context triple: [Troy VI, hasCityWallThickness, up to several meters]
  • A. hasCityWallFunction
    Indicates that an entity serves the functional role of a city wall, such as providing defense, enclosure, or boundary protection for an urban area.
  • B. hasCityWallName
    Indicates that a city wall is associated with a specific name or designation.
  • C. hasCityWallsFrom
    Indicates that a city’s defensive walls originate from, or were constructed starting at, a specified source location or structure.
  • D. cityWallLength
    Indicates the measured length or extent of a city's defensive wall.
  • E. hasCityWallGates
    Indicates that a city wall includes one or more gates that provide passage through it.
  • F. None of above. chosen

Provenance (4 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_69d8e8da8bec819081f400199491ccc3 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6359a7070819099d925447c80bf23 completed April 20, 2026, 2:18 p.m.
PD Predicate disambiguation batch_69e4fd7bd25881908caa04eaef1f6718 completed April 19, 2026, 4:06 p.m.
PDg Predicate description generation batch_69e5004d3a708190a1c13c8f644f3926 completed April 19, 2026, 4:18 p.m.
Created at: April 10, 2026, 1:40 p.m.