Triple
T19571787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freddie Joe Ward |
E489735
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Freddie Joe Ward |
—
|
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: Freddie Joe Ward | Statement: [Freddie Joe Ward, name, Freddie Joe Ward]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freddie Joe Ward Context triple: [Freddie Joe Ward, name, Freddie Joe Ward]
-
A.
Freddie Joe Ward
chosen
Freddie Joe Ward was an American character actor and producer known for his rugged roles in films such as "Tremors," "The Right Stuff," and "Escape from Alcatraz."
-
B.
Freddie Foreman
Freddie Foreman is a notorious former London gangster associated with the Kray twins and the 1960s East End underworld.
-
C.
Freddie Scott
Freddie Scott was an American soul singer and songwriter best known for his 1960s hits like "Hey Girl" and "Are You Lonely for Me."
-
D.
Freddie Taylor
Freddie Taylor is the central protagonist of the British coming-of-age film "Cemetery Junction," a young man struggling to escape his small-town life and find a more meaningful future.
-
E.
Freddie Young
Freddie Young was a renowned British cinematographer best known for his sweeping, visually stunning work on epic films such as "Lawrence of Arabia."
- 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_69d8e8dd9374819098e36349b3211663 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6402103208190b80acdfa82b7a9c4 |
completed | April 20, 2026, 3:02 p.m. |
Created at: April 10, 2026, 1:42 p.m.