Triple
T14886780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elvis (2022 film) |
E350145
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Jeremy Doner |
E350145
|
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: Jeremy Doner | Statement: [Elvis (2022 film), screenwriter, Jeremy Doner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeremy Doner Context triple: [Elvis (2022 film), screenwriter, Jeremy Doner]
-
A.
Jeremy Doner
Jeremy Doner is an American screenwriter known for his work in film and television, including co-writing the screenplay for the biographical drama "Heartbreaker."
-
B.
Jeremy Doner
chosen
Jeremy Doner is a screenwriter best known for co-writing the 2022 biographical musical film "Elvis."
-
C.
Jason Sehorn
Jason Sehorn is a former American football cornerback best known for his NFL career with the New York Giants in the 1990s and early 2000s.
-
D.
Justin Furstenfeld
Justin Furstenfeld is an American singer, songwriter, and guitarist best known as the lead vocalist and primary lyricist of the rock band Blue October.
-
E.
Jeremy Stoppelman
Jeremy Stoppelman is an American entrepreneur best known as the co-founder and longtime CEO of Yelp, a popular online review platform for local businesses.
- 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_69d822ee4f408190b6ac3b2fa434f0df |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded5f5b1c88190815f3585770cb135 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7d554808190a0a87d9f5e225d31 |
completed | May 9, 2026, 4:28 a.m. |
Created at: April 10, 2026, 1:56 a.m.