Triple
T18789034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tippecanoe County |
E459458
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | City of Lafayette |
—
|
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: City of Lafayette | Statement: [Tippecanoe County, contains, City of Lafayette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Lafayette Context triple: [Tippecanoe County, contains, City of Lafayette]
-
A.
Town of Lafayette
The Town of Lafayette is a small municipality in Onondaga County, New York, known for its rural character and proximity to the city of Syracuse.
-
B.
Saint-Louis-du-Sud
Saint-Louis-du-Sud is a coastal commune in southwestern Haiti known for its fishing communities and proximity to historic and natural attractions along the Caribbean Sea.
-
C.
Lafayette
Lafayette is a mid-sized city in southern Louisiana known as a cultural hub of Cajun and Creole music, food, and festivals.
-
D.
Lafayette
Lafayette was a French aristocrat and military officer who became a key general in the American Revolutionary War and a symbol of Franco-American alliance.
-
E.
Lafayette
chosen
Lafayette is a mid-sized city in northwestern Indiana known for its proximity to Purdue University and its role as a regional economic and cultural center.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e59784c5988190851755b7f47835e5 |
completed | April 20, 2026, 3:03 a.m. |
Created at: April 10, 2026, 11:53 a.m.