Triple

T36500824
Position Surface form Disambiguated ID Type / Status
Subject Waterloo Bridge E899320 entity
Predicate constructionWorkforceIncluded P3807 FINISHED
Object large number of women workers 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: large number of women workers | Statement: [Waterloo Bridge, constructionWorkforceIncluded, large number of women workers]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: constructionWorkforceIncluded
Context triple: [Waterloo Bridge, constructionWorkforceIncluded, large number of women workers]
  • A. constructionLabor
    Indicates a relationship where an entity performs or provides labor specifically for construction-related work or projects.
  • B. involvesWorkers chosen
    Indicates that an event, process, or situation includes workers as active participants or affected parties.
  • C. associatedWithWorkforce
    Indicates a relationship in which an entity is connected or related to a particular workforce, such as its members, activities, or management.
  • D. hasWorkforceType
    Indicates the type or category of workforce associated with an entity (such as permanent, temporary, contract, or part-time).
  • E. constructionSite
    Indicates that an entity is a location or area where construction work is actively taking place or is planned to occur.
  • F. None of above.

Provenance (3 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_69f76e5b92088190933afda3f7531dd4 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fddd373cdc8190be1b12e70e4deb1f completed May 8, 2026, 12:55 p.m.
PD Predicate disambiguation batch_69fddc6915a88190ad41e379aa3ede13 completed May 8, 2026, 12:51 p.m.
Created at: May 3, 2026, 4:10 p.m.