Triple
T20885168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Neverwas |
E514257
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | Neverwas |
—
|
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: Neverwas | Statement: [Neverwas, hasTitle, Neverwas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Neverwas Context triple: [Neverwas, hasTitle, Neverwas]
-
A.
Neverwas
chosen
Neverwas is a 2005 fantasy drama film about a psychiatrist who discovers that his father's fictional fairy-tale world may be real, blending psychological mystery with magical realism.
-
B.
Wannweil
Wannweil is a small municipality in the state of Baden-Württemberg in southwestern Germany.
-
C.
Nebelong
Nebelong is a Danish surname most notably associated with 19th-century architect Johan Henrik Nebelong.
-
D.
Noth
Noth is a surname most prominently associated with American actor Chris Noth, known for his roles in television series such as "Sex and the City" and "Law & Order."
-
E.
Verweyhal
Verweyhal is an exhibition hall and cultural venue in Haarlem, Netherlands, known for hosting art and historical exhibitions.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c67c9d1c81908031eb77c124f119 |
completed | April 21, 2026, 12:36 a.m. |
Created at: April 16, 2026, 12:46 p.m.