Triple
T10466936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Claire Tomalin |
E246821
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object | Emily Tomalin |
E246821
|
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: Emily Tomalin | Statement: [Claire Tomalin, hasChild, Emily Tomalin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emily Tomalin Context triple: [Claire Tomalin, hasChild, Emily Tomalin]
-
A.
Susan Abigail Tomalin
Susan Abigail Tomalin, better known as Susan Sarandon, is an Academy Award–winning American actress and activist renowned for her roles in films such as "Thelma & Louise" and "Dead Man Walking."
-
B.
Claire Tomalin
chosen
Claire Tomalin is a British literary journalist and acclaimed biographer known for her works on figures such as Charles Dickens, Samuel Pepys, and Jane Austen.
-
C.
Kathleen Middlekauff
Kathleen Middlekauff is an American academic and former spouse of investigative journalist and author Bob Woodward.
-
D.
Stacy Schiff
Stacy Schiff is a Pulitzer Prize–winning American biographer and essayist known for acclaimed works on figures such as Cleopatra, Vera Nabokov, and the Salem witch trials.
-
E.
Jacqueline Carlin
Jacqueline Carlin is an American actress and former model best known for her film and television work in the 1970s and 1980s.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5092e3230819098ab444f73c9bd40 |
completed | April 7, 2026, 1:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc5c26a88190aab4a590c20191a3 |
completed | April 10, 2026, 11:17 a.m. |
Created at: April 6, 2026, 12:19 p.m.