Triple
T20844840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vector |
E513193
|
entity |
| Predicate | alias |
P39
|
FINISHED |
| Object | Vector |
—
|
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: Vector | Statement: [Vector, alias, Vector]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vector Context triple: [Vector, alias, Vector]
-
A.
Vector
Vector is a mid-range, sport-oriented trim level of the Saab 9-3 that typically offers enhanced performance and upgraded interior and exterior features compared to base models.
-
B.
Vector
Vector is a villainous character from the Despicable Me franchise, known for his orange tracksuit, bowl haircut, and high-tech gadgets.
-
C.
Vector
Vector is a commercial vehicle brand produced by the Russian automotive manufacturer GAZ Group, known primarily for its buses.
-
D.
Vector
Vector is a prominent Nigerian rapper and songwriter known for his intricate wordplay, punchlines, and influential presence in the country’s hip-hop scene.
-
E.
Vectors
"Vectors" is a science fiction work by American author Michael Kube-McDowell, known for its exploration of complex futuristic and technological themes.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c34deef88190992b959b83bc59b1 |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.