Triple
T4505709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ed, Edd n Eddy |
E101326
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Sarah
Sarah is a recurring character in the animated television series "Ed, Edd n Eddy," known as Ed's bossy, temperamental younger sister.
|
E448684
|
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: [Ed, Edd n Eddy, hasCharacter, Sarah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Context triple: [Ed, Edd n Eddy, hasCharacter, Sarah]
-
A.
Sarah
Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
-
B.
Sarah
Sarah is a key matriarch in the Hebrew Bible, revered as the wife of Abraham and mother of Isaac in the Jewish, Christian, and Islamic traditions.
-
C.
Sarah
Sarah is the birth name of Margaret Fuller, the 19th-century American journalist, critic, and women's rights advocate associated with the Transcendentalist movement.
-
D.
Jessica
Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
-
E.
Jessica
Jessica is a feminine given name of Hebrew origin, widely used in English-speaking countries and popularized by Shakespeare’s play "The Merchant of Venice."
- 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: [Ed, Edd n Eddy, hasCharacter, Sarah]
Generated description
Sarah is a recurring character in the animated television series "Ed, Edd n Eddy," known as Ed's bossy, temperamental younger sister.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarah Target entity description: Sarah is a recurring character in the animated television series "Ed, Edd n Eddy," known as Ed's bossy, temperamental younger sister.
-
A.
Sarah
Sarah is a key matriarch in the Hebrew Bible, revered as the wife of Abraham and mother of Isaac in the Jewish, Christian, and Islamic traditions.
-
B.
Sarah
Sarah is the birth name of Margaret Fuller, the 19th-century American journalist, critic, and women's rights advocate associated with the Transcendentalist movement.
-
C.
Sarah
Sarah is the central protagonist of the story "Horse Girl," around whom the main narrative and character development revolve.
-
D.
Jessica
Jessica is a kind-hearted schoolteacher who becomes Mrs. Claus in the classic stop-motion Christmas special "Santa Claus Is Comin' to Town."
-
E.
Jessica
Jessica is a feminine given name of Hebrew origin, widely used in English-speaking countries and popularized by Shakespeare’s play "The Merchant of Venice."
- 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_69bd43d175248190894dc58b5b395c26 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd56ff78748190bb667e70c69dc817 |
completed | March 20, 2026, 2:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bd7f760658819085ca8c631894b486 |
completed | March 20, 2026, 5:10 p.m. |
| NEDg | Description generation | batch_69bd860cb500819082e22070713ed2d4 |
completed | March 20, 2026, 5:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bd867ee76c81909241816ac2045451 |
completed | March 20, 2026, 5:40 p.m. |
Created at: March 20, 2026, 1:01 p.m.