Triple
T14358121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forbes Field |
E356024
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | William Forbes |
E356024
|
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: William Forbes | Statement: [Forbes Field, namedAfter, William Forbes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Forbes Context triple: [Forbes Field, namedAfter, William Forbes]
-
A.
William Forbes
chosen
William Forbes was a prominent Pittsburgh businessman and president of the Pennsylvania Railroad whose name was given to the historic Forbes Field baseball stadium.
-
B.
Louis Forbes
Louis Forbes was a film composer and music director known for scoring numerous Hollywood productions during the mid-20th century.
-
C.
James Forsyth
James Forsyth is a British political journalist and commentator known for his work at outlets such as The Spectator and his connections within UK Conservative Party circles.
-
D.
Robert Forrest
Robert Forrest is the husband of acclaimed American actress Gena Rowlands.
-
E.
John Gillespie
John Gillespie is the husband of American journalist and author Susan Orlean.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f52ca7881908704eef20228aed3 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c48dd408190ac45ad4ca6f610c3 |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:15 a.m.