Triple
T577784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cocoon |
E13793
|
entity |
| Predicate | setIn |
P1393
|
FINISHED |
| Object | Florida |
E549
|
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: Florida | Statement: [Cocoon, setIn, Florida]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Florida Context triple: [Cocoon, setIn, Florida]
-
A.
Florida
chosen
Florida is a southeastern U.S. state known for its warm climate, extensive beaches, tourism industry centered on attractions like Walt Disney World, and significant cultural and economic influence.
-
B.
Esto, Florida
Esto, Florida is a small rural town located in Holmes County in the Florida Panhandle near the Alabama state line.
-
C.
Louisiana
Louisiana is a U.S. state in the Deep South known for its unique Creole and Cajun cultures, the city of New Orleans, and its rich musical and culinary traditions.
-
D.
Georgia
Georgia is a country at the crossroads of Eastern Europe and Western Asia, known for its ancient culture, mountainous landscapes, and historic role along the Silk Road.
-
E.
Georgia
Georgia is a southeastern U.S. state known for its diverse landscapes, historic cities like Atlanta and Savannah, and significant roles in both the Civil War and the civil rights movement.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b69fed88190b5558d4ebd5047a1 |
completed | March 1, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5914232c481909a39cd3373e3c6c9 |
completed | March 2, 2026, 1:31 p.m. |
Created at: March 1, 2026, 7:33 p.m.