Triple
T15328757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Layers |
E366478
|
entity |
| Predicate | featuresArtist |
P1952
|
FINISHED |
| Object |
Lauren Beal
Lauren Beal is an artist known for contributing creative work to the project or publication titled "Layers."
|
E1158425
|
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: Lauren Beal | Statement: [Layers, featuresArtist, Lauren Beal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lauren Beal Context triple: [Layers, featuresArtist, Lauren Beal]
-
A.
Danielle Panabaker
Danielle Panabaker is an American actress best known for her role as Caitlin Snow/Killer Frost in the Arrowverse television series "The Flash."
-
B.
Lauren Boyle
Lauren Boyle is a New Zealand freestyle swimmer and multiple World Championship medallist known for her success in middle- and long-distance events.
-
C.
Melanie Truhett
Melanie Truhett is an American television producer and talent manager known for her work in comedy and for her long-time collaboration and marriage with comedian Brian Posehn.
-
D.
Lauren Graham
Lauren Graham is an American actress and author best known for her starring roles on the television series Gilmore Girls and Parenthood.
-
E.
Natalie Zea
Natalie Zea is an American actress best known for her television work in series such as Justified, The Following, and The Detour.
- 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: Lauren Beal Triple: [Layers, featuresArtist, Lauren Beal]
Generated description
Lauren Beal is an artist known for contributing creative work to the project or publication titled "Layers."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lauren Beal Target entity description: Lauren Beal is an artist known for contributing creative work to the project or publication titled "Layers."
-
A.
Danielle Panabaker
Danielle Panabaker is an American actress best known for her role as Caitlin Snow/Killer Frost in the Arrowverse television series "The Flash."
-
B.
Lauren Boyle
Lauren Boyle is a New Zealand freestyle swimmer and multiple World Championship medallist known for her success in middle- and long-distance events.
-
C.
Melanie Truhett
Melanie Truhett is an American television producer and talent manager known for her work in comedy and for her long-time collaboration and marriage with comedian Brian Posehn.
-
D.
Lauren Graham
Lauren Graham is an American actress and author best known for her starring roles on the television series Gilmore Girls and Parenthood.
-
E.
Natalie Zea
Natalie Zea is an American actress best known for her television work in series such as Justified, The Following, and The Detour.
- 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_69d85a121520819093dcce999fdefe1a |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03dffd6f88190a0f031ee90c6a7d2 |
completed | April 16, 2026, 1:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff2cea6bb88190a6d6f7c55daa4677 |
completed | May 9, 2026, 12:47 p.m. |
| NEDg | Description generation | batch_69ff2d49af388190b2d5526946376264 |
completed | May 9, 2026, 12:49 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff2daa61dc81908b3a8072d6ffa3ee |
completed | May 9, 2026, 12:50 p.m. |
Created at: April 10, 2026, 3:16 a.m.