Triple
T341810
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fred Astaire |
E6852
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Roberta |
E28738
|
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: Roberta | Statement: [Fred Astaire, notableWork, Roberta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberta Context triple: [Fred Astaire, notableWork, Roberta]
-
A.
Roberta
chosen
Roberta is a feminine given name commonly used in various languages, derived from the masculine name Robert.
-
B.
Rita
Rita is a feminine given name used in various cultures, often as a short form of names like Margarita.
-
C.
Barbara
Barbara is a feminine given name of Greek origin that has been widely used in many cultures and languages.
-
D.
Joanna
Joanna is the first name of Joanna Newsom, an American harpist, singer-songwriter, and musician known for her intricate compositions and distinctive vocal style.
-
E.
Angela
Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eae611f88190955fbebe2b01835b |
completed | Feb. 28, 2026, 1:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a3e85ff5248190848e7c390d550c59 |
completed | March 1, 2026, 7:18 a.m. |
Created at: Feb. 28, 2026, 1:08 p.m.