Triple
T14162850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beautiful Creatures |
E350991
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | David Moritz |
E312086
|
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: David Moritz | Statement: [Beautiful Creatures, editor, David Moritz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Moritz Context triple: [Beautiful Creatures, editor, David Moritz]
-
A.
David Moritz
chosen
David Moritz is a film editor known for his work on notable movies including "The Life Aquatic with Steve Zissou."
-
B.
Eduard Meyer
Eduard Meyer was a prominent German historian and classical scholar known for his influential works on ancient history and historiography.
-
C.
Johann David Michaelis
Johann David Michaelis was an 18th-century German biblical scholar and orientalist known for his influential work in Hebrew and Old Testament studies.
-
D.
Gustav Bauer
Gustav Bauer was a German Social Democratic politician who served as Chancellor during the early Weimar Republic.
-
E.
Henry Meybohm
Henry Meybohm was a mountaineer known for participating in the first ascent of Mount Hunter in Alaska.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de613a4a2081908fd51bf4b4d82b6c |
completed | April 14, 2026, 3:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7f3170481909f3981c1e56235d9 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 12:59 a.m.