Triple
T4362583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachael Ray |
E98694
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Rachael |
E220850
|
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: Rachael | Statement: [Rachael Ray, givenName, Rachael]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rachael Context triple: [Rachael Ray, givenName, Rachael]
-
A.
Rachael
chosen
Rachael is a feminine given name commonly used in English-speaking countries, often considered a variant of the biblical name Rachel.
-
B.
Rachael Taylor
Rachael Taylor is an Australian actress known for her roles in films like "Transformers" and TV series such as "Jessica Jones."
-
C.
Rachele
Rachele is an Italian given name, notably borne by Rachele Mussolini, the wife of dictator Benito Mussolini.
-
D.
Trisha
Trisha is a prominent Indian actress best known for her leading roles in Tamil films and her significant impact on South Indian cinema.
-
E.
Charlene
Charlene is a feminine given name derived from the male name Charles.
- 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_69b3454c772081908e20173e379e8ebe |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b351e5ee308190a9271e73689b4a2b |
completed | March 12, 2026, 11:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5dbc68534819095ce62645ca79eff |
completed | March 14, 2026, 10:05 p.m. |
Created at: March 12, 2026, 11:16 p.m.