Triple
T1154515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kimberly |
E23752
|
entity |
| Predicate | hasDiminutive |
P456
|
FINISHED |
| Object | Kimmie |
E23752
|
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: Kimmie | Statement: [Kimberly, hasDiminutive, Kimmie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kimmie Context triple: [Kimberly, hasDiminutive, Kimmie]
-
A.
Kimberly
chosen
Kimberly is a feminine given name of English origin that has been widely used in the United States since the mid-20th century.
-
B.
Kori Rae
Kori Rae is a film producer best known for her work at Pixar Animation Studios, including producing the animated feature "Monsters University."
-
C.
Cailee
Cailee is a feminine given name most notably borne by American actress Cailee Spaeny.
-
D.
Maxine
Maxine is a character featured in the film "Once Again."
-
E.
Chloe
Chloe is an epithet of the Greek goddess Demeter, highlighting her aspect as the bringer of new green growth and flourishing vegetation.
- 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_69a493f0d32c8190ac74bad3c87f2641 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bc8fbb548190865b1bf019f2bde4 |
completed | March 1, 2026, 10:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac8a03f6a0819082cd0e0ea74bb5da |
completed | March 7, 2026, 8:26 p.m. |
Created at: March 1, 2026, 7:44 p.m.