Triple
T12224803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | McHale's Navy |
E291321
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object |
Si Rose
Si Rose was an American television writer and producer best known for co-creating the 1960s military sitcom "McHale's Navy."
|
E972724
|
NE FINISHED |
How this triple was built (4 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: Si Rose | Statement: [McHale's Navy, createdBy, Si Rose]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Si Rose Context triple: [McHale's Navy, createdBy, Si Rose]
-
A.
Rosa
Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
-
B.
Rosa
Rosa is the birth name of Linda Christian, a Mexican film actress known as the first "Bond girl" for her role in the 1954 television adaptation of Casino Royale.
-
C.
Rosa
Rosa is a celebrated poem by Nikki Giovanni that honors civil rights icon Rosa Parks and reflects on the broader struggle for racial justice.
-
D.
Rosa
"Rosa" is a song by Belgian singer-songwriter Jacques Brel, known for its poetic lyrics and emotive, theatrical style characteristic of his chanson repertoire.
-
E.
Rosa
Rosa is a feminine given name of Latin origin meaning "rose," used in many languages and cultures.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Si Rose Triple: [McHale's Navy, createdBy, Si Rose]
Generated description
Si Rose was an American television writer and producer best known for co-creating the 1960s military sitcom "McHale's Navy."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Si Rose Target entity description: Si Rose was an American television writer and producer best known for co-creating the 1960s military sitcom "McHale's Navy."
-
A.
Rosa
Rosa is a genus of flowering plants known for its ornamental roses, prized worldwide for their beauty, fragrance, and cultural symbolism.
-
B.
Rosa
Rosa is the birth name of Linda Christian, a Mexican film actress known as the first "Bond girl" for her role in the 1954 television adaptation of Casino Royale.
-
C.
Rosa
Rosa is a celebrated poem by Nikki Giovanni that honors civil rights icon Rosa Parks and reflects on the broader struggle for racial justice.
-
D.
Rosa
"Rosa" is a song by Belgian singer-songwriter Jacques Brel, known for its poetic lyrics and emotive, theatrical style characteristic of his chanson repertoire.
-
E.
Rosa
Rosa is a feminine given name of Latin origin meaning "rose," used in many languages and cultures.
- F. None of above. chosen
Provenance (5 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca11f788190bad2efb6c83ffccb |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aa9023881909f8373e02d2cad4b |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f61a13fd1481908a06ca65b276e0e1 |
completed | May 2, 2026, 3:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f61ad2bd0c8190ada37bc1f8ae160f |
completed | May 2, 2026, 3:40 p.m. |
Created at: April 8, 2026, 9:51 p.m.