Triple

T13498398
Position Surface form Disambiguated ID Type / Status
Subject ACS-64 E320818 entity
Predicate usedOnService P2367 FINISHED
Object Keystone Service E699716 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: Keystone Service | Statement: [ACS-64, usedOnService, Keystone Service]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Keystone Service
Context triple: [ACS-64, usedOnService, Keystone Service]
  • A. Keystone Service
    Keystone Service is an Amtrak-operated passenger rail service in Pennsylvania that provides frequent regional connections, primarily between Harrisburg and New York City via Philadelphia.
  • B. Keystone
    Keystone is a small tourist town in South Dakota’s Black Hills, best known as the gateway community to Mount Rushmore National Memorial.
  • C. Keystone
    Keystone is a small town located in McDowell County, West Virginia, historically associated with the region’s coal mining industry.
  • D. Keystone chosen
    Keystone is the OpenStack identity service that provides authentication, authorization, and service catalog management for the cloud platform.
  • E. Keystone Earth
    Keystone Earth is the primary, seemingly ordinary version of Earth in Stephen King’s Dark Tower universe, serving as a central hub that other parallel worlds and realities are connected to.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf4fab688190bdc746985b0c7338 completed April 12, 2026, 2:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75485af6c8190a43ccab5449f5014 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:43 p.m.