Triple
T16148026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thirteen Reasons Why |
E391837
|
entity |
| Predicate | authorOfSourceMaterial |
P2806
|
FINISHED |
| Object | Jay Asher |
E801420
|
NE FINISHED |
How this triple was built (2 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: Jay Asher | Statement: [Thirteen Reasons Why, authorOfSourceMaterial, Jay Asher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Asher Context triple: [Thirteen Reasons Why, authorOfSourceMaterial, Jay Asher]
-
A.
Jay Asher
chosen
Jay Asher is an American young adult novelist best known for writing the bestselling and controversial teen suicide-themed novel "Thirteen Reasons Why."
-
B.
Patrick Ness
Patrick Ness is an acclaimed American-born British author best known for his young adult novels such as the "Chaos Walking" trilogy and "A Monster Calls."
-
C.
James Dashner
James Dashner is an American author best known for writing the young adult dystopian science fiction series "The Maze Runner."
-
D.
Michael Grant
Michael Grant is a relatively private individual best known in public records as the former husband of Athena Grant.
-
E.
Stephen Chbosky
Stephen Chbosky is an American novelist, screenwriter, and director best known for creating "The Perks of Being a Wallflower" and directing several major film adaptations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9551e081908391061b092ff31b |
completed | April 17, 2026, 11:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7a9ebf08190aa21cdff051f4ba2 |
completed | May 10, 2026, 3:12 a.m. |
Created at: April 10, 2026, 5:01 a.m.