Triple
T27485
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florida |
E549
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Tallahassee |
E10084
|
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: Tallahassee | Statement: [Florida, contains, Tallahassee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tallahassee Context triple: [Florida, contains, Tallahassee]
-
A.
Tallahassee
chosen
Tallahassee is a city in the Florida Panhandle known for its government institutions, universities, and rolling, forested hills.
-
B.
Orlando
Orlando is a major city in central Florida known for its theme parks, tourism industry, and entertainment attractions.
-
C.
Tampa, Florida
Tampa, Florida is a major city on Florida’s Gulf Coast known for its professional sports teams, port and business center, and role as a key hub in the greater Tampa Bay area.
-
D.
The Magic City
The Magic City is a nickname for Birmingham, Alabama, highlighting its rapid growth during the late 19th and early 20th centuries as an industrial and economic center.
-
E.
Miami
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.
- 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_69a243b4ac2c8190b93c303df797b7b2 |
completed | Feb. 28, 2026, 1:24 a.m. |
| NER | Named-entity recognition | batch_69a2467875048190aad87347c7a1cb67 |
completed | Feb. 28, 2026, 1:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a29817d9d08190aea256b0fbbb2d9b |
completed | Feb. 28, 2026, 7:24 a.m. |
Created at: Feb. 28, 2026, 1:34 a.m.