Triple
T5348833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liza |
E124121
|
entity |
| Predicate | hasDiminutiveForm |
P456
|
FINISHED |
| Object | Liz |
E220458
|
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: Liz | Statement: [Liza, hasDiminutiveForm, Liz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liz Context triple: [Liza, hasDiminutiveForm, Liz]
-
A.
Liz
chosen
Liz is a common shortened form or nickname for the given name Elizabeth.
-
B.
Liza
Liza is a feminine given name most famously associated with American actress and singer Liza Minnelli.
-
C.
Liza Todd
Liza Todd is an American sculptor and the daughter of actress Elizabeth Taylor and producer Mike Todd.
-
D.
Liza Elliott
Liza Elliott is the conflicted, high-powered fashion magazine editor whose psychoanalytic journey drives the plot of the musical "Lady in the Dark."
-
E.
Liza Marshall
Liza Marshall is a British film and television producer known for her work on projects such as "Before I Go to Sleep" and "Temple."
- 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_69bd464be27081908807b40b75c1bbae |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd860ea7088190ad7be14132927d17 |
completed | March 20, 2026, 5:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf21d0d4d08190a33c86553d2012fa |
completed | March 21, 2026, 10:55 p.m. |
Created at: March 20, 2026, 2:01 p.m.