Triple
T10365077
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Live PD |
E244230
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object |
Kimberly Woodard
Kimberly Woodard is a television producer best known for her executive production work on the live law-enforcement reality series "Live PD."
|
E866491
|
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: Kimberly Woodard | Statement: [Live PD, executiveProducer, Kimberly Woodard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kimberly Woodard Context triple: [Live PD, executiveProducer, Kimberly Woodard]
-
A.
Kimberly J. Brown
Kimberly J. Brown is an American actress best known for playing Marnie Piper in Disney Channel’s Halloweentown film series.
-
B.
Angela Quarles
Angela Quarles is a contemporary American author best known for her time-travel and paranormal romance novels.
-
C.
Lynn Petra Alexander
Lynn Petra Alexander is the birth name of Lynn Margulis, the influential American biologist best known for her work on the endosymbiotic theory of eukaryotic cell evolution.
-
D.
Kimberly Wallace
Kimberly Wallace is the sweet, wealthy, and unsuspecting young bride-to-be in the romantic comedy film "My Best Friend's Wedding."
-
E.
Larissa Weems
Larissa Weems is a character from the Netflix series "Wednesday," serving as the poised and enigmatic principal of Nevermore Academy.
- 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: Kimberly Woodard Triple: [Live PD, executiveProducer, Kimberly Woodard]
Generated description
Kimberly Woodard is a television producer best known for her executive production work on the live law-enforcement reality series "Live PD."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kimberly Woodard Target entity description: Kimberly Woodard is a television producer best known for her executive production work on the live law-enforcement reality series "Live PD."
-
A.
Kimberly J. Brown
Kimberly J. Brown is an American actress best known for playing Marnie Piper in Disney Channel’s Halloweentown film series.
-
B.
Angela Quarles
Angela Quarles is a contemporary American author best known for her time-travel and paranormal romance novels.
-
C.
Lynn Petra Alexander
Lynn Petra Alexander is the birth name of Lynn Margulis, the influential American biologist best known for her work on the endosymbiotic theory of eukaryotic cell evolution.
-
D.
Kimberly Wallace
Kimberly Wallace is the sweet, wealthy, and unsuspecting young bride-to-be in the romantic comedy film "My Best Friend's Wedding."
-
E.
Larissa Weems
Larissa Weems is a character from the Netflix series "Wednesday," serving as the poised and enigmatic principal of Nevermore Academy.
- 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_69d381b3e328819094b23b8edcd29b5a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e964a53c8190b748e80850e96656 |
completed | April 7, 2026, 11:24 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d8dc10284c8190bcce0f058b88ef0e |
completed | April 10, 2026, 11:16 a.m. |
| NEDg | Description generation | batch_69d8e50e618c8190a6b597fe511e05de |
completed | April 10, 2026, 11:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d901c7684c8190837ed9ef0c2428af |
completed | April 10, 2026, 1:57 p.m. |
Created at: April 6, 2026, noon