Triple
T22538536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Bissell |
E557220
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bissell |
—
|
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: Bissell | Statement: [Daniel Bissell, familyName, Bissell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bissell Context triple: [Daniel Bissell, familyName, Bissell]
-
A.
Bissell
chosen
Bissell is a surname most notably associated with American intelligence official Richard M. Bissell Jr., a key figure in early CIA covert operations.
-
B.
Bissell Bridge
Bissell Bridge is a highway bridge in Connecticut that carries traffic across the Connecticut River between East Hartford and Windsor.
-
C.
iRobot
iRobot is an American technology company best known for creating the Roomba line of autonomous robotic vacuum cleaners and other consumer robots.
-
D.
Dyson
Dyson is a surname most famously associated with theoretical physicist and mathematician Freeman Dyson, known for his influential work in quantum electrodynamics and futurism.
-
E.
Valetudo
Valetudo is a small, irregular outer moon of Jupiter with a distant, inclined orbit that makes it one of the planet’s more recently discovered natural satellites.
- 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_69e11e58662081909ae346ab384514ca |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f302cd4819098c97ca4fa96363e |
completed | April 29, 2026, 1:30 a.m. |
Created at: April 16, 2026, 8:51 p.m.