Triple
T369495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Havana |
E8236
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Miami |
E1524
|
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: Miami | Statement: [Little Havana, locatedIn, Miami]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miami Context triple: [Little Havana, locatedIn, Miami]
-
A.
Miami
chosen
Miami is a major coastal city in southeastern Florida known for its vibrant nightlife, diverse culture, and role as a global center for finance, tourism, and international trade.
-
B.
Miami Beach
Miami Beach is a coastal resort city in southeastern Florida known for its sandy beaches, Art Deco Historic District, and vibrant nightlife.
-
C.
Miami metropolitan area
The Miami metropolitan area is a major South Florida urban region centered on Miami, known for its large population, cultural diversity, international finance and trade, and status as a gateway to Latin America.
-
D.
Orlando
Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
-
E.
St. Petersburg, Florida
St. Petersburg, Florida is a coastal city on Florida’s Gulf Coast known for its sunny climate, beaches, and vibrant arts and cultural scene.
- 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_69a2e7f2ec648190b42bc7db424f8109 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebfdb0608190b1794a871d0d237a |
completed | Feb. 28, 2026, 1:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a481e969f481908cc6732b4c6aaad6 |
completed | March 1, 2026, 6:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.