Triple
T8489128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bon Voyage |
E200915
|
entity |
| Predicate | title |
P38
|
FINISHED |
| Object |
Bon Voyage
"Bon Voyage" is a widely used title for various creative works, including songs, albums, films, and books, typically evoking themes of farewell and travel.
|
E200915
|
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: Bon Voyage | Statement: [Bon Voyage, title, Bon Voyage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bon Voyage Context triple: [Bon Voyage, title, Bon Voyage]
-
A.
Bon Voyage
"Bon Voyage" is a song by the New Zealand rock band Oceanic.
-
B.
Bon Voyage
Bon Voyage is a retail store, likely themed around travel, that offers related goods and accessories to customers.
-
C.
Le Voyage
"Le Voyage" is the concluding, philosophically charged poem in Charles Baudelaire's collection *Les Fleurs du mal*, exploring themes of escape, disillusionment, and the search for the unknown.
-
D.
Voyage
Voyage is a 1963 Italian drama film directed by Vittorio De Sica, known for its exploration of complex romantic and emotional relationships.
-
E.
Voyage
"Voyage" is a notable work by Sterling Relyea Walter (better known as actor and writer Sterling Hayden), reflecting his adventurous life and seafaring experiences.
- 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: Bon Voyage Triple: [Bon Voyage, title, Bon Voyage]
Generated description
"Bon Voyage" is a widely used title for various creative works, including songs, albums, films, and books, typically evoking themes of farewell and travel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bon Voyage Target entity description: "Bon Voyage" is a widely used title for various creative works, including songs, albums, films, and books, typically evoking themes of farewell and travel.
-
A.
Bon Voyage
chosen
"Bon Voyage" is a song by the New Zealand rock band Oceanic.
-
B.
Bon Voyage
Bon Voyage is a retail store, likely themed around travel, that offers related goods and accessories to customers.
-
C.
Le Voyage
"Le Voyage" is the concluding, philosophically charged poem in Charles Baudelaire's collection *Les Fleurs du mal*, exploring themes of escape, disillusionment, and the search for the unknown.
-
D.
Voyage
"Voyage" is a notable work by Sterling Relyea Walter (better known as actor and writer Sterling Hayden), reflecting his adventurous life and seafaring experiences.
-
E.
Voyage
Voyage is a 1963 Italian drama film directed by Vittorio De Sica, known for its exploration of complex romantic and emotional relationships.
- F. None of above.
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_69ca831d7b148190a6e32c1de43ab13b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe5581d308190b47d76dd49a36529 |
completed | March 31, 2026, 3:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce3a4e5be48190b5c598123ef75f8b |
completed | April 2, 2026, 9:43 a.m. |
| NEDg | Description generation | batch_69ce3d0323248190a076a209df98c96c |
completed | April 2, 2026, 9:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ce3d7909f48190a46f58fca75d7740 |
completed | April 2, 2026, 9:57 a.m. |
Created at: March 30, 2026, 6:13 p.m.