Triple
T15676532
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lara Fabian |
E377456
|
entity |
| Predicate | notableCollaboration |
P8554
|
FINISHED |
| Object |
Maurane
Maurane was a Belgian singer and songwriter renowned for her rich, warm voice and emotive performances in French-language pop and chanson.
|
E1170604
|
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: Maurane | Statement: [Lara Fabian, notableCollaboration, Maurane]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maurane Context triple: [Lara Fabian, notableCollaboration, Maurane]
-
A.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
-
B.
Méjanelle
Méjanelle is a French wine-producing area recognized as a subregion within the broader Languedoc appellation in southern France.
-
C.
Margeride
Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
-
D.
Isloise
Isloise is the French demonym for a female inhabitant of the commune of L’Isle-en-Dodon in southwestern France.
-
E.
Mareva
Mareva is a feminine given name, notably borne by Mareva Grabowski-Mitsotaki, a French-Polynesian businesswoman and former First Lady of Greece.
- 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: Maurane Triple: [Lara Fabian, notableCollaboration, Maurane]
Generated description
Maurane was a Belgian singer and songwriter renowned for her rich, warm voice and emotive performances in French-language pop and chanson.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maurane Target entity description: Maurane was a Belgian singer and songwriter renowned for her rich, warm voice and emotive performances in French-language pop and chanson.
-
A.
Merlav
Merlav is a small island and Oceanic language community in Vanuatu, known for its distinct Mwerlap language and culture.
-
B.
Méjanelle
Méjanelle is a French wine-producing area recognized as a subregion within the broader Languedoc appellation in southern France.
-
C.
Margeride
Margeride is a mountainous and sparsely populated region in south-central France known for its granite plateaus, forests, and traditional rural landscapes.
-
D.
Isloise
Isloise is the French demonym for a female inhabitant of the commune of L’Isle-en-Dodon in southwestern France.
-
E.
Mareva
Mareva is a feminine given name, notably borne by Mareva Grabowski-Mitsotaki, a French-Polynesian businesswoman and former First Lady of Greece.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2e10a4819097eba1ea31e36ac2 |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ee0446881909e9c2504d51d49a3 |
completed | May 9, 2026, 5:29 p.m. |
| NEDg | Description generation | batch_69ff6fb61144819085460226d406161d |
completed | May 9, 2026, 5:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff705b1ea08190bf08b99c19715e57 |
completed | May 9, 2026, 5:35 p.m. |
Created at: April 10, 2026, 4:16 a.m.