Triple
T22355268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry M. Daugherty |
E552634
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Daugherty |
—
|
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: Daugherty | Statement: [Harry M. Daugherty, familyName, Daugherty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daugherty Context triple: [Harry M. Daugherty, familyName, Daugherty]
-
A.
Daugherty
chosen
Daugherty is a surname of Irish origin borne by various notable individuals in sports, politics, and the arts.
-
B.
Daughtrey
Daughtrey is a surname most notably associated with Martha Craig Daughtrey, an American judge who served on the U.S. Court of Appeals for the Sixth Circuit.
-
C.
Coddington
Coddington is an English-origin surname borne by various notable individuals, including early American colonial figures.
-
D.
Haggerty
Haggerty is a surname of Irish origin borne by various notable individuals across fields such as business, politics, and the arts.
-
E.
Darrow
Darrow is a surname most famously associated with Clarence Darrow, the prominent American lawyer and civil libertarian known for high-profile cases in the early 20th 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_69e11e4a0ad08190a385b4d343cf6524 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f157cf94508190b0f2c63ddfecb813 |
completed | April 29, 2026, 12:58 a.m. |
Created at: April 16, 2026, 8:44 p.m.