Triple
T17493060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyrone Township, Michigan |
E425974
|
entity |
| Predicate | countryCode |
P208
|
FINISHED |
| Object | US |
—
|
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 | Statement: [Tyrone Township, Michigan, countryCode, US]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: US Context triple: [Tyrone Township, Michigan, countryCode, US]
-
A.
US
US is the IATA airline designator code assigned to the former American airline US Airways.
-
B.
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.
-
C.
US
The US, or United States, is a large federal republic in North America composed of 50 states and known as one of the world's most influential economic and political powers.
-
D.
US
chosen
The US, or United States of America, is a large federal republic in North America composed of 50 states and known as one of the world's leading economic and military powers.
-
E.
US
US is the commonly used abbreviation for the University of Szczecin, a public higher education institution in Szczecin, Poland.
- 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451d6bd548190b4c6fae27c2a9ae8 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:48 a.m.