Triple
T10353045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Star (automobile) |
E243928
|
entity |
| Predicate | salesRegion |
P12320
|
FINISHED |
| Object | North America |
E335
|
NE FINISHED |
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: North America | Statement: [Star (automobile), salesRegion, North America]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: North America Context triple: [Star (automobile), salesRegion, North America]
-
A.
North America
chosen
North America is a large continent in the Northern and Western Hemispheres that includes countries such as the United States, Canada, and Mexico.
-
B.
Americas
The Americas are the combined landmasses of North and South America, encompassing a vast region of diverse cultures, climates, and ecosystems in the Western Hemisphere.
-
C.
América
América is a popular Mexican professional football club based in Mexico City, widely recognized as one of the most successful and supported teams in Liga MX.
-
D.
América
"América" is a reflective poem by Cuban-American poet Richard Blanco that explores themes of cultural identity, family, and the immigrant experience in the United States.
-
E.
Las Américas
Las Américas is a bus rapid transit station on Line 2 of Mexico City’s Metrobús system, serving passengers in the surrounding urban area.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e949b8e88190ad933399323aed73 |
completed | April 7, 2026, 11:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d794c79ae88190b80c805f7671e264 |
completed | April 9, 2026, noon |
Created at: April 6, 2026, 11:57 a.m.