Triple
T10954312
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smoke Gets in Your Eyes |
E258803
|
entity |
| Predicate | theatricalProduction |
P76889
|
FINISHED |
| Object | Roberta |
E266632
|
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: [Smoke Gets in Your Eyes, theatricalProduction, Roberta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Roberta Context triple: [Smoke Gets in Your Eyes, theatricalProduction, Roberta]
-
A.
Roberta
chosen
"Roberta" is a 1935 Hollywood musical film starring Fred Astaire (Frederick Austerlitz) and Ginger Rogers, known for its fashion-world setting and classic Jerome Kern songs.
-
B.
Roberta
Roberta is a feminine given name commonly used in various languages, derived from the masculine name Robert.
-
C.
Joanne
Joanne is a feminine given name of Hebrew origin, commonly used in English-speaking countries.
-
D.
Roberta Martin
Roberta Martin is a central childhood friend in the coming-of-age film "Now and Then," known for her tomboyish personality and strong, loyal nature within the group.
-
E.
Proberta
Proberta is a small unincorporated community located in Tehama County in Northern California.
- 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d770ff718c81909d4baebea3b56b83 |
completed | April 9, 2026, 9:27 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3447d8cc88190a3e28f204a93a7d3 |
completed | April 18, 2026, 8:44 a.m. |
Created at: April 8, 2026, 9:23 p.m.