Triple
T8871869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paulette Goddard |
E211174
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Kitty |
E179806
|
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: Kitty | Statement: [Paulette Goddard, notableWork, Kitty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kitty Context triple: [Paulette Goddard, notableWork, Kitty]
-
A.
Kitty
Kitty is a common diminutive or nickname for the given name Catherine.
-
B.
Kitty
chosen
"Kitty" is a 1945 historical comedy-drama film set in 18th-century London, best known for starring Paulette Goddard as a pickpocket who rises in society.
-
C.
Katerina Kittycat
Katerina Kittycat is a playful, imaginative kitten and one of Daniel Tiger’s close friends in the children’s animated series "Daniel Tiger’s Neighborhood."
-
D.
Tabby
Tabby is a supporting character in the 2020 supernatural horror film "The Craft: Legacy," which follows a new coven of teenage witches.
-
E.
Mr. Whiskers
Mr. Whiskers is the talking, psychopathic cat companion voiced by Ryan Reynolds in the dark comedy film "The Voices."
- 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_69ca838e78748190934d82db3104f855 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61281e888190a32b08980310979f |
completed | April 1, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfa0f1f1888190a5b514b895e44799 |
completed | April 3, 2026, 11:13 a.m. |
Created at: March 30, 2026, 6:51 p.m.