Triple
T16623544
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justin Crowe |
E403888
|
entity |
| Predicate | createdBy |
P806
|
FINISHED |
| Object | Daniel Knauf |
—
|
NE NERFINISHED |
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: Daniel Knauf | Statement: [Justin Crowe, createdBy, Daniel Knauf]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel Knauf Context triple: [Justin Crowe, createdBy, Daniel Knauf]
-
A.
Daniel Knauf
chosen
Daniel Knauf is an American television writer and producer best known for creating the HBO series "Carnivàle."
-
B.
Paul Knabenshue
Paul Knabenshue was an American diplomat best known for serving as the first U.S. Ambassador to Iraq in the early 20th century.
-
C.
Martin Klotz
Martin Klotz was an Austrian mountaineer known for being one of the first climbers to reach the summit of the Grossglockner, Austria’s highest peak.
-
D.
Erich Krueger
Erich Krueger is the wealthy, enigmatic, and increasingly menacing husband whose obsessive behavior drives the psychological suspense in Mary Higgins Clark’s novel "A Cry in the Night."
-
E.
Martin Kosleck
Martin Kosleck was a German-American character actor best known for playing suave villains and Nazi antagonists in Hollywood films of the 1930s and 1940s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3754f4f508190a5b4b8511623fcd4 |
completed | April 18, 2026, 12:13 p.m. |
Created at: April 10, 2026, 5:17 a.m.