Triple
T20820510
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Vision (2015–2016 miniseries) |
E512560
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Vision |
—
|
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: Vision | Statement: [The Vision (2015–2016 miniseries), mainCharacter, Vision]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vision Context triple: [The Vision (2015–2016 miniseries), mainCharacter, Vision]
-
A.
Vision
chosen
Vision is a powerful, synthetically created superhero in the Marvel universe known for his android body, advanced intellect, and moral complexity.
-
B.
Vision
Vision is Apple’s mixed-reality product line centered on advanced spatial computing headsets like the Apple Vision Pro.
-
C.
Vision Video
Vision Video is a film and video production company known for producing and distributing visual media content.
-
D.
VIS
VIS is the IATA airport code for Visalia Municipal Airport in Visalia, California, United States.
-
E.
VIS
VIS is a large-scale European Union database system used to store and exchange visa application and related biometric data among member states’ authorities.
- 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_69e0b4ce39108190a6e8e5df4f1c8dc5 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2f6a65481909a0df78616e185e4 |
completed | April 21, 2026, 12:21 a.m. |
Created at: April 16, 2026, 12:41 p.m.