Triple
T12356656
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Lover |
E294629
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Sarah
Sarah is a fictional character known as "The Lover," typically portrayed as a passionate, devoted, and emotionally driven romantic figure.
|
E983023
|
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: Sarah | Statement: [The Lover, hasCharacter, Sarah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Context triple: [The Lover, hasCharacter, Sarah]
-
A.
Sarah
Sarah is a recurring character in the animated television series "Ed, Edd n Eddy," known as Ed's bossy, temperamental younger sister.
-
B.
Sarah
Sarah is the given first name of the actress and comedian Patsy Kelly.
-
C.
Sarah
Sarah is the given name of Sarah P. Duke, the philanthropist and namesake of Duke University's Sarah P. Duke Gardens.
-
D.
Sarah
Sarah is the given name of the renowned 19th- and early 20th-century French stage actress Sarah Bernhardt, often called "the Divine Sarah."
-
E.
Sarah
Sarah Onyango Obama was the Kenyan educator and philanthropist best known as the step-grandmother of former U.S. President Barack Obama.
- 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: Sarah Triple: [The Lover, hasCharacter, Sarah]
Generated description
Sarah is a fictional character known as "The Lover," typically portrayed as a passionate, devoted, and emotionally driven romantic figure.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarah Target entity description: Sarah is a fictional character known as "The Lover," typically portrayed as a passionate, devoted, and emotionally driven romantic figure.
-
A.
Sarah
Sarah is a character associated with the work "Bastard," likely serving as a notable figure within its story.
-
B.
Sarah
Sarah is a fictional character from the musical "Ragtime," representing the struggles and resilience of African Americans in early 20th-century America.
-
C.
Sarah
Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
-
D.
Sarah
Sarah is a central character in the psychological horror film "It Comes at Night," portrayed as a protective mother struggling to keep her family safe amid a mysterious, deadly threat.
-
E.
Sarah
Sarah is the resilient and traumatized protagonist of the British horror film "The Descent," known for her harrowing journey through monster-infested caves.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f8e64dc81908c2242c68cd1b86e |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63ee89b28819095e2e5df8acbcb22 |
completed | May 2, 2026, 6:14 p.m. |
| NEDg | Description generation | batch_69f6403711bc8190b214d4b06792a538 |
completed | May 2, 2026, 6:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f640f543c08190b95b16a8909eebf8 |
completed | May 2, 2026, 6:22 p.m. |
Created at: April 8, 2026, 9:54 p.m.