Triple
T7412012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannah Simpson Grant |
E171026
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Clara Grant |
E666524
|
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: Clara Grant | Statement: [Hannah Simpson Grant, relative, Clara Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clara Grant Context triple: [Hannah Simpson Grant, relative, Clara Grant]
-
A.
Clara Grant
chosen
Clara Grant was a 19th-century American woman known primarily as the daughter of U.S. President Ulysses S. Grant and his wife Julia Dent Grant.
-
B.
Clara Bingham
Clara Bingham is an American journalist, author, and documentary producer known for her investigative work on gender, power, and workplace harassment.
-
C.
Clara Clayton
Clara Clayton is a schoolteacher from the Old West and Doc Brown’s love interest in the film "Back to the Future Part III."
-
D.
Clara Jane Bryant
Clara Jane Bryant was an American philanthropist best known as the wife of industrialist and Ford Motor Company founder Henry Ford.
-
E.
Clara Ann Fowler
Clara Ann Fowler, better known by her stage name Patti Page, was a hugely popular American singer and one of the best-selling female artists of the 1950s.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f2a027148190bdb6a7940389e377 |
completed | March 27, 2026, 9:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c4dc1c08190876eb0e70f387b77 |
completed | March 28, 2026, 8:38 p.m. |
Created at: March 27, 2026, 3:11 p.m.