Triple
T5246677
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linda Arvidson |
E118475
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | The New York Hat |
E275535
|
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: The New York Hat | Statement: [Linda Arvidson, notableWork, The New York Hat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The New York Hat Context triple: [Linda Arvidson, notableWork, The New York Hat]
-
A.
The New York Hat
chosen
The New York Hat is a 1912 silent short film directed by D.W. Griffith and starring Mary Pickford, often noted as an early landmark of American narrative cinema.
-
B.
The Man in the Funny Hat
The Man in the Funny Hat is a nickname for legendary Green Bay Packers head coach Vince Lombardi, famed for his leadership, discipline, and multiple NFL championships in the 1960s.
-
C.
Hat Works
Hat Works is a museum in Stockport, England, dedicated to the history and heritage of the hat-making industry.
-
D.
The Man with the Yellow Hat
The Man with the Yellow Hat is the kind, patient caretaker and friend of Curious George in the classic children's book and television series.
-
E.
Opera Hat
Opera Hat is a short story by Clarence Budington Kelland that served as the literary basis for the classic film "Mr. Deeds Goes to Town."
- 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_69bd4468aacc8190a8196f71855cdf4f |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7b5320748190bcf3be4b6c364f92 |
completed | March 20, 2026, 4:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bef832ae8481908a90faf66c1db631 |
completed | March 21, 2026, 7:57 p.m. |
Created at: March 20, 2026, 1:50 p.m.