Triple
T15997729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joel Goldsmith |
E388014
|
entity |
| Predicate | mother |
P120
|
FINISHED |
| Object | Shirley Goldsmith |
E764102
|
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: Shirley Goldsmith | Statement: [Joel Goldsmith, mother, Shirley Goldsmith]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shirley Goldsmith Context triple: [Joel Goldsmith, mother, Shirley Goldsmith]
-
A.
Barbara Gold
Barbara Gold is best known as the former wife of English rock musician Peter Frampton.
-
B.
Shirley Ann Goldsmith
chosen
Shirley Ann Goldsmith was the wife of acclaimed film composer Jerry Goldsmith and a private figure known primarily through her marriage to him.
-
C.
Barbara Goldsmith
Barbara Goldsmith was an American author, journalist, and philanthropist known for her influential works of narrative history and her advocacy for human rights and freedom of expression.
-
D.
Marion Goldin
Marion Goldin is an American television news producer best known for her long tenure on the CBS newsmagazine "60 Minutes."
-
E.
Suzanne Goldish
Suzanne Goldish is a television and film producer, also known professionally as Suzie Gold, recognized for her work behind the scenes in entertainment production.
- 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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e157893ebc8190acb75ee05e450fae |
completed | April 16, 2026, 9:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006ec9fb3881908df8d3d318cbd238 |
completed | May 10, 2026, 11:40 a.m. |
Created at: April 10, 2026, 4:55 a.m.