Triple
T22031019
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cigar Mile Handicap |
E544084
|
entity |
| Predicate | countryCode |
P208
|
FINISHED |
| Object | USA |
—
|
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: USA | Statement: [Cigar Mile Handicap, countryCode, USA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: USA Context triple: [Cigar Mile Handicap, countryCode, USA]
-
A.
USA
USA is a public research university located in Mobile, Alabama, known for its diverse academic programs and regional impact in the Gulf Coast area.
-
B.
USA
chosen
USA is the three-letter International Olympic Committee country code representing the United States of America in international sporting events.
-
C.
US
US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
-
D.
US
US is the commonly used abbreviation for the University of Seville, a major public research university located in Seville, Spain.
-
E.
US
The US, or United States, is a federal republic in North America comprising 50 states and known as one of the world's largest economic and military powers.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127edd5b48190a9aeb2840105c181 |
completed | April 28, 2026, 9:34 p.m. |
Created at: April 16, 2026, 8:24 p.m.