Triple
T7161125
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jacqueline Logan |
E166945
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Jacqueline Logan |
E166945
|
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 Logan | Statement: [Jacqueline Logan, name, Jacqueline Logan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jacqueline Logan Context triple: [Jacqueline Logan, name, Jacqueline Logan]
-
A.
Jacqueline Logan
chosen
Jacqueline Logan was an American silent film actress best known for her prominent roles in 1920s Hollywood cinema.
-
B.
Roberta Logan
Roberta Logan is a fictional character appearing in the mystery film "Mr. Wong in Chinatown."
-
C.
Amy Logan
Amy Logan is a fictional character featured in the film score for the movie "Erased."
-
D.
Virginia Kelley
Virginia Kelley was the mother of former U.S. President Bill Clinton and a nurse anesthetist from Arkansas whose life and memoir gained public attention during and after her son's political rise.
-
E.
Melissa Rivers
Melissa Rivers is an American television host, producer, and actress best known for her red carpet coverage and for continuing the comedic legacy of her mother, Joan Rivers.
- 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e82ce770819081dccf7ffd50c2ab |
completed | March 27, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adc08b688190a00024727542c8b9 |
completed | March 28, 2026, 10:30 a.m. |
Created at: March 27, 2026, 2:47 p.m.