Triple
T14575305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mary Pugh |
E342026
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mary Pugh |
E342026
|
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: Mary Pugh | Statement: [Mary Pugh, name, Mary Pugh]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mary Pugh Context triple: [Mary Pugh, name, Mary Pugh]
-
A.
Mary Pugh
chosen
Mary Pugh is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Pugh.
-
B.
Marian Pugh
Marian Pugh is best known as the spouse of prominent Australian painter Clifton Pugh.
-
C.
Margaret Pumphrey
Margaret Pumphrey was the wife of British-born American actor Victor McLaglen, an Academy Award–winning star of early 20th-century cinema.
-
D.
Sarah Pugh
Sarah Pugh was a prominent 19th-century American abolitionist and women's rights advocate based in Philadelphia.
-
E.
Mary Fawcett
Mary Fawcett was the mother of British academic and politician Henry Fawcett, a noted 19th-century economist and Postmaster General.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f49d58819094fcd2a702e146cb |
completed | April 14, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002d92c9788190aa4523a1e47bc561 |
completed | May 10, 2026, 7:02 a.m. |
Created at: April 10, 2026, 1:24 a.m.