Triple
T834970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love (novel) |
E18049
|
entity |
| Predicate | centralCharacter |
P9202
|
FINISHED |
| Object |
Junior
Junior is the protagonist of the novel "Love" by Toni Morrison, around whom the story’s complex relationships and themes of desire, memory, and power revolve.
|
E97636
|
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: Junior | Statement: [Love (novel), centralCharacter, Junior]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Junior Context triple: [Love (novel), centralCharacter, Junior]
-
A.
Junior
Junior is a 1994 comedy film in which Arnold Schwarzenegger plays a scientist who becomes pregnant as part of an experimental fertility project.
-
B.
Young
Young is a regional town in New South Wales, Australia, historically known for its gold rush heritage and cherry production.
-
C.
Min
Min is a common given name of Chinese origin used for both males and females.
-
D.
Entered Apprentice
Entered Apprentice is the first and introductory degree of Freemasonry, representing a candidate’s initial initiation into the Masonic fraternity.
-
E.
Child
Child is a common English surname borne by various notable individuals, including the famed American chef and television personality Julia Child.
- 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: Junior Triple: [Love (novel), centralCharacter, Junior]
Generated description
Junior is the protagonist of the novel "Love" by Toni Morrison, around whom the story’s complex relationships and themes of desire, memory, and power revolve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Junior Target entity description: Junior is the protagonist of the novel "Love" by Toni Morrison, around whom the story’s complex relationships and themes of desire, memory, and power revolve.
-
A.
Junior
Junior is a 1994 comedy film in which Arnold Schwarzenegger plays a scientist who becomes pregnant as part of an experimental fertility project.
-
B.
Young
Young is a regional town in New South Wales, Australia, historically known for its gold rush heritage and cherry production.
-
C.
Min
Min is a common given name of Chinese origin used for both males and females.
-
D.
Entered Apprentice
Entered Apprentice is the first and introductory degree of Freemasonry, representing a candidate’s initial initiation into the Masonic fraternity.
-
E.
Child
Child is a common English surname borne by various notable individuals, including the famed American chef and television personality Julia Child.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2b66c908190a52f731119b77a1e |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d9b57fc8190981ed4eeb2ac5548 |
completed | March 3, 2026, 11:24 p.m. |
| NEDg | Description generation | batch_69a782fae3f48190b27e5f0aefa1dd70 |
completed | March 4, 2026, 12:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a7838451348190838910e90866a1f0 |
completed | March 4, 2026, 12:57 a.m. |
Created at: March 1, 2026, 7:38 p.m.