Triple
T10721314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liv Ullmann |
E252827
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Sofie |
E130110
|
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: Sofie | Statement: [Liv Ullmann, notableWork, Sofie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sofie Context triple: [Liv Ullmann, notableWork, Sofie]
-
A.
Sophie
chosen
Sophie is a feminine given name of Greek origin, commonly used in many countries and meaning "wisdom."
-
B.
Astrid
Astrid is a Belgian princess and member of the country’s royal family.
-
C.
Ottilia
Ottilia is a feminine given name of Germanic origin, related to Otto and typically interpreted to mean "wealth" or "prosperity."
-
D.
Maddalene
Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
-
E.
Leonie
Leonie is a feminine given name of European origin, commonly used in German- and French-speaking countries and derived from the Latin word for "lion."
- 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_69d6aa5d8be481909a43218b2bfdbe95 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d70d43655081909b071100c96cb4f6 |
completed | April 9, 2026, 2:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dbb72b9ce08190a9134f3365d3f8cb |
completed | April 12, 2026, 3:15 p.m. |
Created at: April 8, 2026, 9:13 p.m.