Triple
T11995463
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexis Denisof |
E285516
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Grimm |
E358672
|
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: Grimm | Statement: [Alexis Denisof, notableWork, Grimm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grimm Context triple: [Alexis Denisof, notableWork, Grimm]
-
A.
Grimm
Grimm is a German surname most famously associated with the Brothers Grimm, Jacob and Wilhelm, renowned for their collection of folk and fairy tales.
-
B.
Grimm
chosen
Grimm is a dark fantasy police procedural television series that blends crime-solving with folklore-inspired supernatural elements.
-
C.
Grimm’s Enchanted Forest
Grimm’s Enchanted Forest is a fairy-tale themed area in Europa-Park that immerses visitors in scenes and characters from the classic Brothers Grimm stories.
-
D.
Company of Wolves
Company of Wolves is a film production company known for its involvement in British cinema projects such as the 2002 adaptation of "Nicholas Nickleby."
-
E.
The Witch
The Witch is a 2015 atmospheric horror film set in 17th-century New England that follows a Puritan family menaced by sinister forces in the wilderness.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903b211688190bfe6dd15c3f96d2f |
completed | April 10, 2026, 2:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f48ad06350819094180403858db172 |
completed | May 1, 2026, 11:13 a.m. |
Created at: April 8, 2026, 9:46 p.m.