Triple
T628945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annie Besant |
E15882
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Annie |
E76744
|
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: Annie | Statement: [Annie Besant, givenName, Annie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Annie Context triple: [Annie Besant, givenName, Annie]
-
A.
Annie
chosen
Annie is a popular Broadway musical, later adapted into a film, about an optimistic orphan girl in 1930s New York.
-
B.
Chiquitita
"Chiquitita" is a popular 1979 pop ballad by Swedish group ABBA, known for its uplifting melody and comforting lyrics about offering support in times of sadness.
-
C.
Mary Jane Gumm
Mary Jane Gumm was an American vaudeville and film performer, best known as one of Judy Garland’s older sisters and early singing partners in the Gumm Sisters act.
-
D.
Meet Me in St. Louis
Meet Me in St. Louis is a classic 1944 American musical film set in early 20th-century St. Louis, following the lives and romances of the Smith family in the lead-up to the 1904 World's Fair.
-
E.
National Velvet
National Velvet is a classic 1944 family sports drama film about a young girl and her horse competing in the Grand National steeplechase.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e5b5a308190a62165f9275e2f5f |
completed | March 1, 2026, 8:15 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a56938be6481909a8eba01f5d856c1 |
completed | March 2, 2026, 10:40 a.m. |
Created at: March 1, 2026, 7:35 p.m.