Triple
T3882696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia |
E92860
|
entity |
| Predicate | spellingVariant |
P457
|
FINISHED |
| Object | Júlia |
E196347
|
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: Júlia | Statement: [Julia, spellingVariant, Júlia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Júlia Context triple: [Julia, spellingVariant, Júlia]
-
A.
Júlia
chosen
Júlia is the given name of Julia Warhola, the mother of American pop artist Andy Warhol.
-
B.
Julianna
Julianna is a feminine given name most notably borne by American actress Julianna Margulies.
-
C.
Mária
Mária is the Hungarian and Slovak form of the given name Mary, commonly used in Central and Eastern Europe.
-
D.
Johanna
Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
-
E.
Johanna
"Johanna" is a recurring, lyrically poignant love song from Stephen Sondheim's musical *Sweeney Todd: The Demon Barber of Fleet Street*.
- 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeec8e8b3481909617ca0e37f8a6d4 |
completed | March 9, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b51c8983b88190a716987f44487d56 |
completed | March 14, 2026, 8:30 a.m. |
Created at: March 9, 2026, 3:20 p.m.