Triple
T18738749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Sullivan |
E458234
|
entity |
| Predicate | isFrom |
P11553
|
FINISHED |
| Object | United States |
—
|
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: United States | Statement: [Dan Sullivan, isFrom, United States]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: United States Context triple: [Dan Sullivan, isFrom, United States]
-
A.
United States of America
chosen
The United States of America is a large federal republic in North America known for its global political, economic, military, and cultural influence.
-
B.
Usa
Usa is a city in Ōita Prefecture, Japan, known for the historic Usa Jingū Shinto shrine.
-
C.
USA
USA is the three-letter International Olympic Committee country code representing the United States of America in international sporting events.
-
D.
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.
-
E.
Usan
Usan is a small coastal village in Angus, Scotland, known for its fishing heritage and scenic North Sea shoreline.
- 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_69e5768ca990819098102f8522ce401f |
completed | April 20, 2026, 12:42 a.m. |
Created at: April 10, 2026, 11:51 a.m.