Triple

T6700054
Position Surface form Disambiguated ID Type / Status
Subject Lancaster Veterans Memorial Library E152855 entity
Predicate city P40 FINISHED
Object Lancaster E114102 NE 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: Lancaster | Statement: [Lancaster Veterans Memorial Library, city, Lancaster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lancaster
Context triple: [Lancaster Veterans Memorial Library, city, Lancaster]
  • A. Lancaster
    Lancaster is a historic city in North West England known for its medieval castle, Georgian architecture, and role as the county town of Lancashire.
  • B. Lancaster chosen
    Lancaster is a city in northern Los Angeles County, California, known for its location in the Antelope Valley of the Mojave Desert and its aerospace and renewable energy industries.
  • C. Lancaster
    Lancaster is a small community in eastern Ontario, Canada, located near the Quebec border along the St. Lawrence River.
  • D. Lancaster
    Lancaster was the original settlement that later developed into the city of Lincoln, the capital of Nebraska.
  • E. Lancaster
    Lancaster is an English surname most famously associated with the American actor Burt Lancaster.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c68807adbc8190b8632df42b39eda0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d0a7355081908a0acfa8d2bb4c09 completed March 27, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7b97210819086e88624c476fa24 completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:05 p.m.