Triple
T20118340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melanie |
E490528
|
entity |
| Predicate | birthName |
P65
|
FINISHED |
| Object |
Melanie Anne Safka
Melanie Anne Safka is an American singer-songwriter best known for her 1970s folk-pop hits such as "Brand New Key" and her performance at Woodstock.
|
E1411110
|
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: Melanie Anne Safka | Statement: [Melanie, birthName, Melanie Anne Safka]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melanie Anne Safka Context triple: [Melanie, birthName, Melanie Anne Safka]
-
A.
Melanie Miller
Melanie Miller is a film and television producer known for her work on projects such as the documentary "Navalny."
-
B.
Melanie Holland
Melanie Holland is the central protagonist of the novel "Strong Motion," around whom the story’s personal and environmental crises unfold.
-
C.
Melanie
Melanie is a supporting character in the comedy film "Grumpy Old Men," involved in the small-town relationships and humorous conflicts that drive the story.
-
D.
Melanie
Melanie is a feminine given name commonly used in various countries and languages.
-
E.
Melanie
Melanie is a central character in Anita Desai’s novel "Fasting, Feasting," whose experiences reflect the constraints and expectations placed on women within a traditional Indian family.
- 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: Melanie Anne Safka Triple: [Melanie, birthName, Melanie Anne Safka]
Generated description
Melanie Anne Safka is an American singer-songwriter best known for her 1970s folk-pop hits such as "Brand New Key" and her performance at Woodstock.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Melanie Anne Safka Target entity description: Melanie Anne Safka is an American singer-songwriter best known for her 1970s folk-pop hits such as "Brand New Key" and her performance at Woodstock.
-
A.
Melanie Miller
Melanie Miller is a film and television producer known for her work on projects such as the documentary "Navalny."
-
B.
Melanie Holland
Melanie Holland is the central protagonist of the novel "Strong Motion," around whom the story’s personal and environmental crises unfold.
-
C.
Melanie
Melanie is a feminine given name commonly used in various countries and languages.
-
D.
Melanie
Melanie is a supporting character in the comedy film "Grumpy Old Men," involved in the small-town relationships and humorous conflicts that drive the story.
-
E.
Melanie
Melanie is the given first name of British actress Thandiwe Newton, who was previously credited professionally as Thandie Newton.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6673c32bc8190a52875961fbcc5e2 |
completed | April 20, 2026, 5:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08271de03c81908f669f712ca1233a |
completed | May 16, 2026, 8:13 a.m. |
| NEDg | Description generation | batch_6a08280f9e70819091682323b55ca855 |
completed | May 16, 2026, 8:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08288d98fc8190a146f43a027682f0 |
completed | May 16, 2026, 8:19 a.m. |
Created at: April 11, 2026, 11:30 p.m.