Triple
T4626074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Fan |
E101099
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Christian Wagner |
E197182
|
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: Christian Wagner | Statement: [The Fan, editedBy, Christian Wagner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Christian Wagner Context triple: [The Fan, editedBy, Christian Wagner]
-
A.
Christian Wagner
chosen
Christian Wagner is a film editor known for his work on major Hollywood productions, including the superhero film "The Suicide Squad."
-
B.
Max Wagner
Max Wagner was an American character actor known for his prolific work in Hollywood films from the 1920s through the 1970s, often appearing in supporting and uncredited roles.
-
C.
Wolfram von Soden
Wolfram von Soden was a German Assyriologist renowned for his influential work on Akkadian lexicography and the history of ancient Mesopotamia.
-
D.
Nal Kalchbrenner
Nal Kalchbrenner is a computer scientist and machine learning researcher known for co-developing WaveNet, a groundbreaking deep generative model for raw audio.
-
E.
Alberich Zwyssig
Alberich Zwyssig was a Swiss monk and composer best known for writing the music to the Swiss national anthem, the "Swiss Psalm."
- 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_69bd43d0497c8190ac23c65c5804846a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a0a7b588190bc6552ee5babb198 |
completed | March 20, 2026, 2:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfaab30508190881828adab92ba22 |
completed | March 21, 2026, 1:55 a.m. |
Created at: March 20, 2026, 1:13 p.m.