Triple
T32731922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porsche Cayman (987/981) |
E836977
|
entity |
| Predicate | generationIncludes |
P146063
|
FINISHED |
| Object | Porsche Cayman 987 |
—
|
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: Porsche Cayman 987 | Statement: [Porsche Cayman (987/981), generationIncludes, Porsche Cayman 987]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generationIncludes Context triple: [Porsche Cayman (987/981), generationIncludes, Porsche Cayman 987]
-
A.
generationTechnology
Indicates the technology or method used to generate or produce something (e.g., power, data, or content).
-
B.
generation
Indicates the relationship in which one entity produces, creates, or brings another entity into existence.
-
C.
generationOf
Indicates that one entity is the origin, creator, or producer of another entity.
-
D.
characterGenerator
Indicates a relationship where an entity produces, defines, or initializes characters or character data for use in another context.
-
E.
generationInSeries
chosen
Indicates that one entity is a specific generation or installment within an ordered series or sequence of related entities.
- 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_69f34935fb048190ad4967420581f835 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:11 a.m.