Triple
T21879231
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CATS |
E540233
|
entity |
| Predicate | governingBody |
P46
|
FINISHED |
| Object | City of Charlotte |
—
|
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 Charlotte | Statement: [CATS, governingBody, City of Charlotte]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: City of Charlotte Context triple: [CATS, governingBody, City of Charlotte]
-
A.
Charlotte
Charlotte is a major city in North Carolina known as a financial hub and home to numerous universities and corporate campuses.
-
B.
Charlotte
Charlotte is a major city in North Carolina known for its financial industry, rapid growth, and cultural institutions.
-
C.
Charlotte
chosen
Charlotte is the largest city in North Carolina, known as a major U.S. financial hub and home to several professional and collegiate sports teams.
-
D.
Charlotte
Charlotte is a feminine given name of French and English origin, traditionally used as the female form of Charles and borne by numerous queens, nobles, and notable figures.
-
E.
Charlotte
Charlotte is the wise and compassionate spider from E.B. White's classic children's novel "Charlotte's Web," known for saving Wilbur the pig by weaving words into her web.
- 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_69e0c479a98081908ce333853fdd4348 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f118e42c108190b6308016655c429e |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 16, 2026, 7:03 p.m.