Triple
T18735730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropark station |
E458156
|
entity |
| Predicate | servedBy |
P82
|
FINISHED |
| Object | Keystone Service |
—
|
NE NERFINISHED |
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: [Metropark station, servedBy, Keystone Service]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Keystone Service Context triple: [Metropark station, servedBy, Keystone Service]
-
A.
Keystone Service
chosen
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
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 (2 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_69d8d394dc308190b6725073f5db324c |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d7ae10081908bc6857d1d147eef |
completed | April 20, 2026, 12:04 a.m. |
Created at: April 10, 2026, 11:51 a.m.