Triple
T22732473
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elon Law |
E562171
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Elon Law |
—
|
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: Elon Law | Statement: [Elon Law, shortName, Elon Law]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elon Law Context triple: [Elon Law, shortName, Elon Law]
-
A.
Elon Law
chosen
Elon Law is the law school of Elon University in North Carolina, known for its experiential, practice-oriented legal education and accelerated 2.5-year J.D. program.
-
B.
Elon J. Farnsworth
Elon J. Farnsworth was a Union cavalry officer in the American Civil War, best known for his controversial and fatal charge at Gettysburg in 1863.
-
C.
Tony Lawson
Tony Lawson is a film editor known for his work on major motion pictures, including the drama "The Brave One."
-
D.
Andrew Lawson
Andrew Lawson was a pioneering early 20th-century geologist best known for his foundational work on California’s geology and seismic activity, including identifying the San Andreas Fault.
-
E.
Michael T. Ross
Michael T. Ross is an American rock keyboardist known for his work with bands such as Hardline and Lita Ford.
- 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_69e24550859c81908727d91efc3a81b4 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1792ef5bc819088af71bdc96ed41b |
completed | April 29, 2026, 3:21 a.m. |
Created at: April 17, 2026, 3:21 p.m.