Triple
T9996916
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jenny Slate as Dawn Bellwether |
E197223
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | JaredBush |
E201574
|
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: JaredBush | Statement: [Jenny Slate as Dawn Bellwether, createdBy, JaredBush]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JaredBush Context triple: [Jenny Slate as Dawn Bellwether, createdBy, JaredBush]
-
A.
Jared Bush
chosen
Jared Bush is an American screenwriter and director best known for his work on Disney animated films such as Zootopia, Moana, and Encanto.
-
B.
Jared Stern
Jared Stern is an American screenwriter, producer, and director known for his work on animated films such as DC League of Super-Pets and contributions to various family-oriented comedies.
-
C.
Jared Kaplan
Jared Kaplan is a theoretical physicist and AI researcher known for his work on deep learning scaling laws and contributions to large language model development.
-
D.
Jared
Jared is a village located in Pakistan’s scenic Kaghan Valley, known for its mountainous landscapes and tourism.
-
E.
Jared
Jared is the given name of Jared Diamond, an American geographer, historian, and author best known for his Pulitzer Prize–winning book "Guns, Germs, and Steel."
- 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_69ca82f3b61c81908ecc2c1c96dbc2e4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdcc8aa1a881909879a694496f11a5 |
completed | April 2, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2820063f48190886619fe26b0cc94 |
completed | April 5, 2026, 3:38 p.m. |
Created at: March 30, 2026, 8:51 p.m.