Triple
T17990831
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flickering Lights |
E430364
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Anders Villadsen |
—
|
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: Anders Villadsen | Statement: [Flickering Lights, editedBy, Anders Villadsen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anders Villadsen Context triple: [Flickering Lights, editedBy, Anders Villadsen]
-
A.
Anders Villadsen
chosen
Anders Villadsen is a film editor best known for his work on the Danish black comedy drama "Adam's Apples."
-
B.
Morten Ristorp
Morten Ristorp is a Danish songwriter and producer known for his work on international pop and R&B hits.
-
C.
Stig Petersen
Stig Petersen is a researcher and scientist known for co-authoring a 2021 Nature paper led by Jumper and colleagues, likely in the field of computational biology or protein structure prediction.
-
D.
Terje Hansen
Terje Hansen is an academic author known for co-authoring scholarly work with prominent economist and mathematician Herbert Scarf.
-
E.
Morten Giese
Morten Giese is a Danish film editor and director known for his work on the thriller "Nightwatch" (1994) and various other Scandinavian film and television projects.
- 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_69d8b90364248190a37381adea932f42 |
completed | April 10, 2026, 8:46 a.m. |
| NER | Named-entity recognition | batch_69e4b29f127c81908b0c4cb3787e002c |
completed | April 19, 2026, 10:46 a.m. |
Created at: April 10, 2026, 10:23 a.m.