Triple
T30658887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porsche 911 R (991) |
E780466
|
entity |
| Predicate | weightReduction |
P148133
|
FINISHED |
| Object | approximately 50 kg |
—
|
LITERAL FINISHED |
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: approximately 50 kg | Statement: [Porsche 911 R (991), weightReduction, approximately 50 kg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weightReduction Context triple: [Porsche 911 R (991), weightReduction, approximately 50 kg]
-
A.
weightReductionComparedTo
Indicates a comparison showing how much less weight one entity has relative to another.
-
B.
cutDown
Indicates that an agent causes something standing or elevated (such as a tree or structure) to fall or be reduced by cutting.
-
C.
reduction
chosen
Indicates a relationship where something is decreased in amount, size, intensity, or degree compared to a prior state or reference.
-
D.
weight
Indicates a relationship where a numerical value quantifies how heavy an entity is, often used to measure or compare mass or load.
-
E.
وزن
Indicates a relationship where one entity has, measures, or is characterized by a certain weight or mass.
- F. None of above.
Provenance (3 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_69f224a6d10481909290be1a00fc83b3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68adf0f908190aba108c90a766428 |
completed | May 2, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69f6861170d08190bb98be609d436f84 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:30 p.m.