Triple
T21688964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shelly |
E535306
|
entity |
| Predicate | shortFormOf |
P43
|
FINISHED |
| Object | Rochelle |
—
|
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: Rochelle | Statement: [Shelly, shortFormOf, Rochelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rochelle Context triple: [Shelly, shortFormOf, Rochelle]
-
A.
Rochelle
Rochelle is the full given name of Chellie Pingree, an American politician serving as a U.S. Representative from Maine.
-
B.
Rochelle
chosen
Rochelle is the tough, outspoken, and fiercely protective mother of Chris in the sitcom "Everybody Hates Chris," known for her strict parenting and sharp humor.
-
C.
Rochelle
Rochelle, better known as Shelly Sterling, is an American businesswoman and co-owner of the Los Angeles Clippers who gained national attention during the Donald Sterling controversy.
-
D.
Laurel
Laurel is a feminine given name of English origin, derived from the laurel tree traditionally associated with honor and victory.
-
E.
Laurel
Laurel is a small city in Maryland known for its suburban character and location between Washington, D.C. and Baltimore.
- 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_69e0c469b6ec8190aee4cadd1527db91 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef96cd51d481908df67e4f69826b06 |
completed | April 27, 2026, 5:03 p.m. |
Created at: April 16, 2026, 6:44 p.m.