Triple
T12169043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rob Ford |
E289906
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Renata Ford |
E289906
|
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: Renata Ford | Statement: [Rob Ford, spouse, Renata Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Renata Ford Context triple: [Rob Ford, spouse, Renata Ford]
-
A.
Renata Ford
chosen
Renata Ford is a Canadian businesswoman and the widow of former Toronto mayor Rob Ford.
-
B.
Renata Klein
Renata Klein is a wealthy, high-powered executive and fiercely protective mother featured in the television series "Big Little Lies."
-
C.
Margo Dydek
Margo Dydek was a towering Polish professional basketball center renowned as one of the greatest shot-blockers in WNBA history.
-
D.
Renata Kallosh
Renata Kallosh is a theoretical physicist known for her influential work in supergravity, string theory, and cosmology.
-
E.
Renata
Renata is a young Venetian woman who becomes the poignant love interest of an aging American colonel in Ernest Hemingway’s novel "Across the River and Into the Trees."
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d85c088190a74fb7590877659b |
completed | April 10, 2026, 3:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60a85e42481908c5517a24f7688e0 |
completed | May 2, 2026, 2:30 p.m. |
Created at: April 8, 2026, 9:50 p.m.