Triple
T21320937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barons Court tube station |
E525611
|
entity |
| Predicate | architect |
P184
|
FINISHED |
| Object | Harry W. Ford |
—
|
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: Harry W. Ford | Statement: [Barons Court tube station, architect, Harry W. Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harry W. Ford Context triple: [Barons Court tube station, architect, Harry W. Ford]
-
A.
Harry W. Ford
chosen
Harry W. Ford was an architect known for his work on London Underground stations in the early 20th century.
-
B.
Luke Ford
Luke Ford is an Australian actor best known for his roles in film and television, including a prominent part in the crime drama "Animal Kingdom."
-
C.
Robert Newton Ford
Robert Newton Ford was an American outlaw best known for killing Jesse James, an act that made him infamous in the history of the Old West.
-
D.
Leon Ford
Leon Ford is an Australian actor, writer, and director known for his work in film, television, and theatre.
-
E.
Burtt Harris
Burtt Harris is a film producer best known for his work on the acclaimed crime drama "Prince of the City."
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ed1538c8190954da114e49dfa36 |
completed | April 21, 2026, 1:42 p.m. |
Created at: April 16, 2026, 4:39 p.m.