Triple

T4424065
Position Surface form Disambiguated ID Type / Status
Subject Rosa Parks: My Story E95167 entity
Predicate focusesOnLocation P31 FINISHED
Object Montgomery, Alabama E9524 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: Montgomery, Alabama | Statement: [Rosa Parks: My Story, focusesOnLocation, Montgomery, Alabama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Montgomery, Alabama
Context triple: [Rosa Parks: My Story, focusesOnLocation, Montgomery, Alabama]
  • A. Montgomery, Alabama chosen
    Montgomery, Alabama is the state capital known as a pivotal center of the American civil rights movement, including events such as the Montgomery Bus Boycott.
  • B. Montgomery
    Montgomery is a historic market town in Powys, Wales, known for its medieval castle ruins and Georgian architecture.
  • C. Montgomery
    Montgomery is a common English and Scottish surname of Norman origin, historically associated with nobility and military figures.
  • D. Gadsden, Alabama
    Gadsden, Alabama is a small industrial city in northeastern Alabama known historically for its manufacturing plants and labor history.
  • E. Moody, Alabama
    Moody, Alabama is a small suburban city in central Alabama that forms part of the Birmingham metropolitan area.
  • 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_69b3453a36908190b95a79a297ca083c completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b3554ca5208190ba2661616dcf071c completed March 13, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69b66b29cbe4819083788fe6e3e8ba3b completed March 15, 2026, 8:17 a.m.
Created at: March 12, 2026, 11:30 p.m.