Triple
T10486499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maxine Cooper |
E247311
|
entity |
| Predicate | notableRole |
P22
|
FINISHED |
| Object | Velda |
E211461
|
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: Velda | Statement: [Maxine Cooper, notableRole, Velda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Velda Context triple: [Maxine Cooper, notableRole, Velda]
-
A.
Velda
chosen
Velda is the loyal and resourceful secretary and love interest of private investigator Mike Hammer in the hardboiled crime novel and film "Kiss Me Deadly."
-
B.
Venora
Venora is the surname of American actress Diane Venora, known for her work in film, television, and theater.
-
C.
Vereya
Vereya is a small historic town in Russia that was once part of the former Moscow Governorate.
-
D.
Wyulda
Wyulda is a genus of Australian marsupials commonly known as scaly-tailed possums, characterized by their prehensile tails and arboreal lifestyle.
-
E.
Vana
Vana is a diminutive or nickname commonly used for the given name Silvana.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5096988ec81908d7518b09256c145 |
completed | April 7, 2026, 1:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc8c73748190b97c78af6cf142d9 |
completed | April 10, 2026, 11:18 a.m. |
Created at: April 6, 2026, 12:23 p.m.