Triple
T3192174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilene Woods |
E66847
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Jacqueline |
E134483
|
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: Jacqueline | Statement: [Ilene Woods, givenName, Jacqueline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jacqueline Context triple: [Ilene Woods, givenName, Jacqueline]
-
A.
Jacqueline
chosen
Jacqueline is a feminine given name most famously borne by former U.S. First Lady Jacqueline Kennedy Onassis.
-
B.
Patricia
Patricia is a feminine given name of Latin origin, commonly used in English-speaking countries.
-
C.
Laura Jeanne
Laura Jeanne is the birth name of American actress and producer Reese Witherspoon, known for films like "Legally Blonde" and "Walk the Line."
-
D.
Jacqueline Feather
Jacqueline Feather is a screenwriter best known for her work on films such as the 1982 musical comedy "Starstruck."
-
E.
Madelyn
Madelyn is a feminine given name, often considered a modern variant of Madeline and commonly used in English-speaking countries.
- 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_69ad8588ba18819086a10951c32ecb80 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6e8e4b48190bc7c6443fc6da900 |
completed | March 8, 2026, 4:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b276fbb7c481909097f5af619e45f4 |
completed | March 12, 2026, 8:19 a.m. |
Created at: March 8, 2026, 3:07 p.m.