Triple
T18984661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francis Russell |
E464523
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Russell |
—
|
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: Russell | Statement: [Francis Russell, familyName, Russell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Russell Context triple: [Francis Russell, familyName, Russell]
-
A.
Russell
chosen
Russell is a common English surname most famously associated with legendary Boston Celtics basketball player and civil rights activist Bill Russell.
-
B.
Russell
Russell is the enthusiastic young Wilderness Explorer who befriends elderly widower Carl Fredricksen in Pixar's animated film "Up."
-
C.
Russell
Russell is a sharp-tongued, wisecracking young member of the Junkyard Gang in the animated series "Fat Albert and the Cosby Kids."
-
D.
Russell
Russell is a rural municipality in eastern Ontario, Canada, known for its bilingual (English and French) community and proximity to Ottawa.
-
E.
Russell
Russell is the middle name of Rensselaer Russell Nelson, an American jurist who served as a United States federal judge in the 19th century.
- 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_69d8dd008af48190a97ff1c6488edf1b |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d65ec0bc8190b878252b1b4c3620 |
completed | April 20, 2026, 7:31 a.m. |
Created at: April 10, 2026, 12:01 p.m.