Triple
T16130611
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Haas |
E391384
|
entity |
| Predicate | notableStudent |
P4838
|
FINISHED |
| Object | Karl Teeter |
—
|
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: Karl Teeter | Statement: [Mary Haas, notableStudent, Karl Teeter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Karl Teeter Context triple: [Mary Haas, notableStudent, Karl Teeter]
-
A.
Karl V. Teeter
chosen
Karl V. Teeter was an American linguist known for his influential work documenting and analyzing Native American languages, particularly those of Northern California.
-
B.
George Shumway
George Shumway is a fictional character from the satirical comic strip "Ernie Pook's Comeek" by Lynda Barry.
-
C.
John Pardue
John Pardue is a cinematographer known for his work on film and television projects, including the 2012 television film "The Girl."
-
D.
George Ratterman
George Ratterman was an American professional football quarterback who later became a prominent sports broadcaster and attorney.
-
E.
George Ratliff
George Ratliff is an American film director and screenwriter known for his work in psychological thrillers and character-driven dramas.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2020829e88190b51ab32d22cf0259 |
completed | April 17, 2026, 9:48 a.m. |
Created at: April 10, 2026, 5:01 a.m.