Triple
T171056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judy Garland |
E3121
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Liza Minnelli |
E23314
|
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: Liza Minnelli | Statement: [Judy Garland, influenced, Liza Minnelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liza Minnelli Context triple: [Judy Garland, influenced, Liza Minnelli]
-
A.
Liza Minnelli
chosen
Liza Minnelli is an American actress and singer best known for her Academy Award-winning performance in the film "Cabaret" and her powerful stage presence in musical theatre and concerts.
-
B.
Bette Midler
Bette Midler is an American singer, actress, and comedian renowned for her powerful vocals, theatrical performances, and acclaimed work in film, television, and on stage.
-
C.
Judy Garland
Judy Garland was an iconic American actress and singer best known for her role as Dorothy in "The Wizard of Oz" and her powerful, emotionally expressive performances on stage and screen.
-
D.
Lorraine Gary
Lorraine Gary is an American actress best known for playing Ellen Brody in the Jaws film series.
-
E.
Maxine Singer
Maxine Singer is an American molecular biologist renowned for her pioneering work in genetics and for her leadership in shaping ethical guidelines for recombinant DNA research.
- 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_69a2524ce1e48190ab066bf72859f474 |
completed | Feb. 28, 2026, 2:26 a.m. |
| NER | Named-entity recognition | batch_69a258b94d00819098e90bdfa1306f9f |
completed | Feb. 28, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a305e3686c8190a6124673b83187d9 |
completed | Feb. 28, 2026, 3:12 p.m. |
Created at: Feb. 28, 2026, 2:34 a.m.