Triple
T9739826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ember Lumen |
E236156
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Peter Sohn |
E77016
|
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: Peter Sohn | Statement: [Ember Lumen, createdBy, Peter Sohn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter Sohn Context triple: [Ember Lumen, createdBy, Peter Sohn]
-
A.
Peter Sohn
chosen
Peter Sohn is an American animator, voice actor, and film director at Pixar known for his work on projects like "Ratatouille," "The Good Dinosaur," and "Elemental."
-
B.
Il-woo Jung
Il-woo Jung is a Korean individual notable enough to be recognized as a prominent bearer of the surname Jung.
-
C.
Yohan Lee
Yohan Lee is a fictional character from the work "The Encyclopedists."
-
D.
Yong-joon Jung
Yong-joon Jung is a notable individual recognized for achievements significant enough to be distinctly associated with the surname Jung.
-
E.
Woo-sung Jung
Woo-sung Jung is a prominent South Korean actor and film producer known for his leading roles in action and drama films such as "Beat," "The Good, the Bad, the Weird," and "Steel Rain."
- 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_69ca84d313e88190983ee6ffd0ef60d2 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f29a5bc8190b2b391017405c71e |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1afe0dab48190832ab77265c09d70 |
completed | April 5, 2026, 12:42 a.m. |
Created at: March 30, 2026, 8:22 p.m.