Triple
T18449765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anna Leopoldowna |
E450748
|
entity |
| Predicate | given name |
P17
|
FINISHED |
| Object | Anna |
—
|
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: Anna | Statement: [Anna Leopoldowna, given name, Anna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Context triple: [Anna Leopoldowna, given name, Anna]
-
A.
Anna
chosen
Anna is the given name of Anna Murray Douglass, an African American abolitionist and the first wife of Frederick Douglass.
-
B.
Anna
Anna is a character from the "Predator" franchise, appearing as one of the human figures caught up in the deadly encounters with the extraterrestrial hunter.
-
C.
Anna
Anna is a supporting character in Hector Berlioz’s grand opera *Les Troyens*, typically portrayed as Dido’s loyal sister and confidante.
-
D.
Anna
Anna is the popular nickname of C. N. Annadurai, a prominent Indian politician, writer, and founder of the Dravida Munnetra Kazhagam (DMK) party who served as Chief Minister of Tamil Nadu.
-
E.
Anna
Anna is a central fictional character in Michael Ondaatje's novel "Divisadero," around whom much of the story's emotional and narrative complexity revolves.
- 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_69d8d38345688190b565eac2e4cd7935 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5264748dc8190984501af3e4b2036 |
completed | April 19, 2026, 7 p.m. |
Created at: April 10, 2026, 11:30 a.m.