Triple
T13517100
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tea with Mussolini |
E322789
|
entity |
| Predicate | hasCostumeDesigner |
P36430
|
FINISHED |
| Object | Anna Anni |
E322789
|
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: Anna Anni | Statement: [Tea with Mussolini, hasCostumeDesigner, Anna Anni]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Anni Context triple: [Tea with Mussolini, hasCostumeDesigner, Anna Anni]
-
A.
Anna Anni
chosen
Anna Anni was an Italian costume designer known for her work on films such as "Tea with Mussolini."
-
B.
Anika
Anika is the first name of Anika Noni Rose, an American actress and singer best known for voicing Tiana in Disney’s "The Princess and the Frog."
-
C.
Anju Mallige
Anju Mallige is a notable work by acclaimed Indian playwright and filmmaker Girish Karnad.
-
D.
Bhavani Kooduthurai
Bhavani Kooduthurai is a well-known riverbank confluence area near Erode in Tamil Nadu, India, where major rivers meet and attract pilgrims and visitors.
-
E.
Raisa
Raisa Gorbacheva was the influential and highly visible wife of Soviet leader Mikhail Gorbachev, known for her intellectual background, public role, and charitable work.
- 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_69d80766a21881909f21a1b7421d3b8a |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbafa0ed508190b2855171b1945e84 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f75496496c819093a9e763d293bcf7 |
completed | May 3, 2026, 1:58 p.m. |
Created at: April 9, 2026, 9:44 p.m.