Triple
T21652981
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michaela |
E534386
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Micaela |
—
|
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: Micaela | Statement: [Michaela, hasVariant, Micaela]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Micaela Context triple: [Michaela, hasVariant, Micaela]
-
A.
Mikaela
chosen
Mikaela is a feminine given name most prominently associated with American alpine ski champion Mikaela Shiffrin.
-
B.
Eliana
Eliana is a feminine given name of Hebrew and Latin origin, often interpreted to mean "God has answered" or "my God has answered."
-
C.
Manoela
Manoela is a feminine given name, commonly used in Portuguese- and Spanish-speaking countries, that is related to the name Manoel/Manuel.
-
D.
Noelia
Noelia is a feminine given name, commonly used in Spanish-speaking countries and derived from the name Noel.
-
E.
Penelope Alvarez
Penelope Alvarez is the Cuban-American single mother and military veteran at the heart of the 2017 reboot of "One Day at a Time," navigating family life, mental health, and cultural identity with humor and resilience.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
Created at: April 16, 2026, 6:36 p.m.