Triple
T15595563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sylvie Vartan |
E374883
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
La Maritza
"La Maritza" is a popular French song by Sylvie Vartan, celebrated as one of her signature hits from the late 1960s.
|
E1167123
|
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: La Maritza | Statement: [Sylvie Vartan, notableWork, La Maritza]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La Maritza Context triple: [Sylvie Vartan, notableWork, La Maritza]
-
A.
Blanquita
Blanquita is the namesake figure—likely an influential woman or performer—after whom Mexico City’s historic Teatro Blanquita was named.
-
B.
Mariquita
Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
-
C.
Del Carmen
Del Carmen is a coastal municipality on Siargao Island in the Philippines, known for its mangrove forests and access to popular surfing and island-hopping destinations.
-
D.
Haydée
Haydée is a fictional Greek princess and former slave who becomes a devoted ally and love interest of Edmond Dantès in Alexandre Dumas' novel "The Count of Monte Cristo."
-
E.
Santamaría
Santamaría is a Spanish-language surname borne by various notable figures in Latin American history and culture.
- 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: La Maritza Triple: [Sylvie Vartan, notableWork, La Maritza]
Generated description
"La Maritza" is a popular French song by Sylvie Vartan, celebrated as one of her signature hits from the late 1960s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: La Maritza Target entity description: "La Maritza" is a popular French song by Sylvie Vartan, celebrated as one of her signature hits from the late 1960s.
-
A.
Blanquita
Blanquita is the namesake figure—likely an influential woman or performer—after whom Mexico City’s historic Teatro Blanquita was named.
-
B.
Mariquita
Mariquita is a historic town in central Colombia known as an early colonial settlement and former mining center.
-
C.
Del Carmen
Del Carmen is a coastal municipality on Siargao Island in the Philippines, known for its mangrove forests and access to popular surfing and island-hopping destinations.
-
D.
Haydée
Haydée is a fictional Greek princess and former slave who becomes a devoted ally and love interest of Edmond Dantès in Alexandre Dumas' novel "The Count of Monte Cristo."
-
E.
Santamaría
Santamaría is a Spanish-language surname borne by various notable figures in Latin American history and culture.
- 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_69d85cce25008190b13b52745fbd719b |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e5f9db8819083abf80f01f32b3d |
completed | April 16, 2026, 2:50 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff56ca72ec8190a237db843dc6d625 |
completed | May 9, 2026, 3:46 p.m. |
| NEDg | Description generation | batch_69ff58a93fb481908cedf981caf1bb23 |
completed | May 9, 2026, 3:54 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff59718048819086a1d0ba773e9a92 |
completed | May 9, 2026, 3:57 p.m. |
Created at: April 10, 2026, 4:12 a.m.