Triple
T2296525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tony James |
E51627
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Amabel James |
E51627
|
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: Amabel James | Statement: [Tony James, spouse, Amabel James]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amabel James Context triple: [Tony James, spouse, Amabel James]
-
A.
Amabel James
chosen
Amabel James is known as the spouse of British businessman and hedge fund manager Tony James.
-
B.
Sarah H. Joslyn
Sarah H. Joslyn was a prominent Omaha philanthropist whose generosity and patronage of the arts led to the creation of the Joslyn Art Museum.
-
C.
Lucy Ann Shaler
Lucy Ann Shaler was the wife of American naval officer and War of 1812 hero Commodore Thomas Macdonough.
-
D.
Louisa E. Masterson
Louisa E. Masterson was a family member of famed Old West lawman and gambler Bat Masterson, known primarily through her relation to him.
-
E.
Maria Bissell Hotchkiss
Maria Bissell Hotchkiss was an American philanthropist best known for endowing and establishing the prestigious Hotchkiss School in Lakeville, Connecticut.
- 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_69a88b0a9f248190bcff941463d8f65a |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc5ddf00081909acb47cbd9a5f20e |
completed | March 7, 2026, 6:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd566575a88190a03a306fbe40f8c9 |
completed | March 20, 2026, 2:15 p.m. |
Created at: March 4, 2026, 7:49 p.m.