Triple
T21199664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TVML |
E522418
|
entity |
| Predicate | relatedTechnology |
P1485
|
FINISHED |
| Object | Swift |
—
|
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: Swift | Statement: [TVML, relatedTechnology, Swift]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Swift Context triple: [TVML, relatedTechnology, Swift]
-
A.
Swift
chosen
Swift is a modern, compiled programming language developed by Apple for building fast, safe, and expressive applications across its platforms and beyond.
-
B.
Swift
Swift is a NASA space telescope mission dedicated to detecting and rapidly observing gamma-ray bursts and other high-energy astrophysical phenomena.
-
C.
Swift
Swift is a British single-seat fighter aircraft developed in the early Cold War era, known for its swept-wing design and service with the Royal Air Force.
-
D.
Swift
"Swift" is a jazz fusion album by British pianist and composer Bill Laurance, known for its intricate compositions and blend of acoustic and electronic textures.
-
E.
Swift
Swift is a popular compact hatchback car produced by Maruti Suzuki, known for its sporty design and fuel efficiency.
- 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_69e0b51061388190aa03f19700d3ef04 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7342fe3a08190b7ed2cadf60091a8 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 3:17 p.m.