Triple
T20323906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McKean County |
E492282
|
entity |
| Predicate | ISOCode |
P208
|
FINISHED |
| Object | US-PA |
—
|
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: US-PA | Statement: [McKean County, ISOCode, US-PA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: US-PA Context triple: [McKean County, ISOCode, US-PA]
-
A.
Pennsylvania
chosen
Pennsylvania is a historically significant U.S. state in the Mid-Atlantic and Northeastern regions, known for cities like Philadelphia and Pittsburgh and its central role in the nation’s founding.
-
B.
Penn
Penn is a picturesque village in Buckinghamshire, England, known for its historic church, traditional Chilterns architecture, and scenic countryside setting.
-
C.
Penn
Penn is the middle name of Robert Penn Warren, the influential American poet, novelist, and first U.S. Poet Laureate.
-
D.
Penn
Penn is a prominent American family name most famously associated with actor and filmmaker Sean Penn and his relatives in the entertainment industry.
-
E.
Penn
Penn is a private Ivy League research university in Philadelphia known for its strong programs in business, law, medicine, and the liberal arts.
- 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_69e0b4a0134081909113563e1c3ba68a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6778e59508190bfd7a3ce44d56a93 |
completed | April 20, 2026, 6:59 p.m. |
Created at: April 16, 2026, 11:21 a.m.