Triple

T2529309
Position Surface form Disambiguated ID Type / Status
Subject Edward Tilley E56116 entity
Predicate residenceBeforeMigration P4907 FINISHED
Object Leiden E14108 NE FINISHED

How this triple was built (3 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: Leiden | Statement: [Edward Tilley, residenceBeforeMigration, Leiden]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leiden
Context triple: [Edward Tilley, residenceBeforeMigration, Leiden]
  • A. Leiden chosen
    Leiden is a historic Dutch city in South Holland known for its prestigious university, rich cultural heritage, and well-preserved canals and old town.
  • B. Utrecht
    Utrecht is a historic city and province in the central Netherlands, known for its medieval old town, canals, and role as a religious and cultural center.
  • C. Nijmegen
    Nijmegen is a historic Dutch city near the German border that played a crucial strategic role during World War II, particularly in the Allied advance in 1944.
  • D. Groningen
    Groningen is a historic province in the northern Netherlands, known for its university city of the same name, flat landscapes, and rich maritime and agricultural heritage.
  • E. Haarlem
    Haarlem is a historic Dutch city in the province of North Holland, known for its medieval architecture, cultural heritage, and role as a regional center near Amsterdam.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: residenceBeforeMigration
Context triple: [Edward Tilley, residenceBeforeMigration, Leiden]
  • A. formerResidenceOf chosen
    Indicates that a location was once the place where a person or entity lived or was based, but is no longer their current residence.
  • B. cityPreviouslyLocatedIn
    Indicates that a city was formerly situated within a specified location or administrative region, but is no longer located there.
  • C. residenceDuringLife
    Indicates that an entity lived or resided in a particular place during some period of its lifetime.
  • D. hasResidenceIn
    Indicates that an entity lives or maintains a primary dwelling in a specified location.
  • E. residenceDuringCareer
    Indicates the place where an individual lived for a significant period while pursuing their professional career.
  • F. None of above.

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_69ab4a48e4f081908f1218d244608659 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd25903f08190b46e12d32278daca completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69c8e55a6d848190856460c45374c629 completed March 29, 2026, 8:39 a.m.
PD Predicate disambiguation batch_69abd0c2e34c8190a914d5c2afba147c completed March 7, 2026, 7:16 a.m.
Created at: March 6, 2026, 9:46 p.m.