Triple
T22451023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrew Herr |
E554988
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Andrew Herr |
—
|
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: Andrew Herr | Statement: [Andrew Herr, name, Andrew Herr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrew Herr Context triple: [Andrew Herr, name, Andrew Herr]
-
A.
Andrew Herr
chosen
Andrew Herr is a Canadian actor best known for playing Jonesy, one of the hockey players, on the comedy series "Letterkenny."
-
B.
Andrew Harr
Andrew Harr is a songwriter and music producer best known as one half of the production duo The Runners, who have worked on numerous hip-hop and R&B hits.
-
C.
Andrew Hynes
Andrew Hynes was an American military officer and early Kentucky pioneer known for his role in the region’s frontier development.
-
D.
Chris Healey
Chris Healey is a computer scientist known for his work in information visualization and visual analytics.
-
E.
Andrew Hutchinson
Andrew Hutchinson was a historical figure significant enough in local or regional history that Hutchinson County was named in his honor.
- 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_69e11e5113208190ab58c6b595f9d1d0 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15b4ba6a88190a0a79e2c20fa8c08 |
completed | April 29, 2026, 1:13 a.m. |
Created at: April 16, 2026, 8:48 p.m.