Triple
T19542155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liza Huber |
E488932
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Liza |
—
|
NE NERFINISHED |
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 | Statement: [Liza Huber, givenName, Liza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liza Context triple: [Liza Huber, givenName, Liza]
-
A.
Liza
chosen
Liza is a feminine given name most famously associated with American actress and singer Liza Minnelli.
-
B.
Liza
Liza is a central tragic heroine in Alexander Pushkin’s short story "The Queen of Spades," whose ill-fated love and entanglement with gambling intrigue drive much of the plot.
-
C.
Love Liza
Love Liza is a 2002 independent drama film starring Philip Seymour Hoffman as a grieving widower spiraling into gasoline huffing after his wife's suicide.
-
D.
Liza Miller
Liza Miller is the 40-year-old divorced mother who pretends to be in her twenties to restart her publishing career in the TV series "Younger."
-
E.
Liza Rey
Liza Rey is a musician and harpist known for her work in jazz and popular music, as well as for being part of a prominent musical family.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8db5b6c8190984b61f91981f575 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6387442588190a2cdae60a6a940d6 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 10, 2026, 1:41 p.m.