Triple
T7437904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Park |
E171665
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Paige Hunter
Paige Hunter is a fictional protagonist featured in a narrative set in and around New York City's Central Park.
|
E664492
|
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: Paige Hunter | Statement: [Central Park, mainCharacter, Paige Hunter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paige Hunter Context triple: [Central Park, mainCharacter, Paige Hunter]
-
A.
Paige Hurd
Paige Hurd is an American actress best known for her roles in television series such as "Everybody Hates Chris" and "The Oval," as well as various film appearances.
-
B.
Paige Meade
Paige Meade is an actress known for her role in the British science-fiction comedy film "Attack the Block."
-
C.
Paige Alexander
Paige Alexander is an American nonprofit leader and former U.S. government official who serves as the chief executive officer of The Carter Center.
-
D.
Paige Howard
Paige Howard is an American actress known for her work in film, television, and theater, and as a member of the Howard entertainment family.
-
E.
Paige Moss
Paige Moss is an American actress best known for her roles in 1990s teen films and television series, including a supporting role in the ensemble comedy "Can’t Hardly Wait."
- 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: Paige Hunter Triple: [Central Park, mainCharacter, Paige Hunter]
Generated description
Paige Hunter is a fictional protagonist featured in a narrative set in and around New York City's Central Park.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Paige Hunter Target entity description: Paige Hunter is a fictional protagonist featured in a narrative set in and around New York City's Central Park.
-
A.
Paige Hurd
Paige Hurd is an American actress best known for her roles in television series such as "Everybody Hates Chris" and "The Oval," as well as various film appearances.
-
B.
Paige Meade
Paige Meade is an actress known for her role in the British science-fiction comedy film "Attack the Block."
-
C.
Paige Alexander
Paige Alexander is an American nonprofit leader and former U.S. government official who serves as the chief executive officer of The Carter Center.
-
D.
Paige Howard
Paige Howard is an American actress known for her work in film, television, and theater, and as a member of the Howard entertainment family.
-
E.
Paige Moss
Paige Moss is an American actress best known for her roles in 1990s teen films and television series, including a supporting role in the ensemble comedy "Can’t Hardly Wait."
- 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_69c68a64228c8190affaec2a8127ce7b |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f34aa3388190ac300cf934042d78 |
completed | March 27, 2026, 9:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8278cd9cc8190b88767c1432b3007 |
completed | March 28, 2026, 7:10 p.m. |
| NEDg | Description generation | batch_69c828854f6c8190885afb60d789f9b9 |
completed | March 28, 2026, 7:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c82926c16c8190adf364f7b9d3c149 |
completed | March 28, 2026, 7:16 p.m. |
Created at: March 27, 2026, 3:13 p.m.