Triple
T19040600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rochelle Pingree |
E465989
|
entity |
| Predicate | givenName |
P17
|
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: [Rochelle Pingree, givenName, Rochelle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rochelle Context triple: [Rochelle Pingree, givenName, Rochelle]
-
A.
Rochelle
chosen
Rochelle is the full given name of Chellie Pingree, an American politician serving as a U.S. Representative from Maine.
-
B.
Rochelle
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.
Laurel
Laurel is a feminine given name of English origin, derived from the laurel tree traditionally associated with honor and victory.
-
D.
Laurel
Laurel is a small city in Maryland known for its suburban character and location between Washington, D.C. and Baltimore.
-
E.
Laurel
Laurel is a small city in southern Montana, known as a residential and industrial community near Billings and a gateway to outdoor recreation in the Yellowstone region.
- 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_69d8dd0359648190bc2a9202c5cf29d2 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d80054c88190a9d3a49aed504235 |
completed | April 20, 2026, 7:38 a.m. |
Created at: April 10, 2026, 12:02 p.m.