Triple
T13721464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rina |
E329046
|
entity |
| Predicate | shortFor |
P43
|
FINISHED |
| Object |
Serena
Serena is a feminine given name commonly used in various cultures, often associated with calmness and serenity.
|
E1058300
|
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: Serena | Statement: [Rina, shortFor, Serena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serena Context triple: [Rina, shortFor, Serena]
-
A.
Serena
Serena is a central character in George Gershwin's opera "Porgy and Bess," known as a strong, devout woman who provides emotional and moral support within the Catfish Row community.
-
B.
Serena
Serena was a prominent noblewoman of the late Western Roman Empire, known as the influential wife of the powerful general Stilicho and a member of the imperial Theodosian dynasty.
-
C.
Serena
"Serena" is a 2014 period drama film directed by Susanne Bier, starring Jennifer Lawrence and Bradley Cooper as a married couple whose timber empire unravels in Depression-era North Carolina.
-
D.
Serena
Serena is one of Elle Woods’ bubbly and supportive Delta Nu sorority sisters in the Broadway musical adaptation of "Legally Blonde."
-
E.
Serena Ryder
Serena Ryder is a Canadian singer-songwriter known for her soulful vocals and genre-blending folk, rock, and pop music.
- 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: Serena Triple: [Rina, shortFor, Serena]
Generated description
Serena is a feminine given name commonly used in various cultures, often associated with calmness and serenity.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Serena Target entity description: Serena is a feminine given name commonly used in various cultures, often associated with calmness and serenity.
-
A.
Serena
Serena is a central character in George Gershwin's opera "Porgy and Bess," known as a strong, devout woman who provides emotional and moral support within the Catfish Row community.
-
B.
Serena
Serena was a prominent noblewoman of the late Western Roman Empire, known as the influential wife of the powerful general Stilicho and a member of the imperial Theodosian dynasty.
-
C.
Serena
"Serena" is a 2014 period drama film directed by Susanne Bier, starring Jennifer Lawrence and Bradley Cooper as a married couple whose timber empire unravels in Depression-era North Carolina.
-
D.
Serena
Serena is one of Elle Woods’ bubbly and supportive Delta Nu sorority sisters in the Broadway musical adaptation of "Legally Blonde."
-
E.
Serena Ryder
Serena Ryder is a Canadian singer-songwriter known for her soulful vocals and genre-blending folk, rock, and pop music.
- 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_69d80770b9bc81909f70c8c317d53cff |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69de01f3b46481909ceedfa78e9ca92b |
completed | April 14, 2026, 8:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f79d5e1ecc8190a9fec550a99702c0 |
completed | May 3, 2026, 7:09 p.m. |
| NEDg | Description generation | batch_69f79e9e6ff88190b031fb1403cacabc |
completed | May 3, 2026, 7:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7a2d6e7ec81908a4cbc324e793c24 |
completed | May 3, 2026, 7:32 p.m. |
Created at: April 9, 2026, 9:55 p.m.