Triple
T6141513
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Navin Field |
E136972
|
entity |
| Predicate | owner |
P347
|
FINISHED |
| Object | Frank Navin |
E576980
|
NE FINISHED |
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: Frank Navin | Statement: [Navin Field, owner, Frank Navin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Navin Context triple: [Navin Field, owner, Frank Navin]
-
A.
Frank Navin
chosen
Frank Navin was an American baseball executive best known as the longtime owner and president of the Detroit Tigers in the early 20th century.
-
B.
Philip Hart
Philip Hart was a prominent U.S. Senator from Michigan known for his strong advocacy of civil rights and government reform.
-
C.
Hartland Snyder
Hartland Snyder was an American theoretical physicist known for his early work on black hole physics and for being one of J. Robert Oppenheimer’s notable doctoral students.
-
D.
Jean Peters
Jean Peters was an American film actress best known for her leading roles in 1940s and 1950s Hollywood adventure and drama films.
-
E.
James Nourse
James Nourse was an 18th-century British sea captain involved in the transatlantic slave trade.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cb2404c8190bbbfa78d5f49389f |
completed | March 22, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c5e3c26a9c8190a7dfbe0895461d3b |
completed | March 27, 2026, 1:56 a.m. |
Created at: March 22, 2026, 4:16 p.m.