Triple
T18201128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Fielder |
E435787
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Fielder |
—
|
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: Fielder | Statement: [Prince Fielder, familyName, Fielder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fielder Context triple: [Prince Fielder, familyName, Fielder]
-
A.
Fielder
chosen
Fielder is the surname of Prince Fielder, a former Major League Baseball slugger known for his power hitting and multiple All-Star selections.
-
B.
Fielder Cook
Fielder Cook was an American film and television director known for his work on acclaimed TV movies and adaptations, particularly during the mid-20th century.
-
C.
Fielder Jones
Fielder Jones was an early 20th-century Major League Baseball manager and outfielder best known for leading the Chicago White Sox to a championship in the dead-ball era.
-
D.
Sybrand
Sybrand is a Dutch masculine given name most notably borne by politician Sybrand van Haersma Buma.
-
E.
Gunner Boone
Gunner Boone is the young protagonist of the fantasy drama film "The Water Man," who embarks on a perilous quest to find a mythical figure he believes can save his ailing mother.
- 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e0d71f288190918ca78543118bbe |
completed | April 19, 2026, 2:04 p.m. |
Created at: April 10, 2026, 10:32 a.m.