Triple
T2292898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford S550 platform |
E51544
|
entity |
| Predicate | introducedForModelYear |
P4161
|
FINISHED |
| Object | 2015 model year |
—
|
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: 2015 model year | Statement: [Ford S550 platform, introducedForModelYear, 2015 model year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedForModelYear Context triple: [Ford S550 platform, introducedForModelYear, 2015 model year]
-
A.
introducedInYear
Indicates the year in which something was first introduced, launched, or made available.
-
B.
demonstrationYear
Indicates the year in which a demonstration, display, or public showing of something took place.
-
C.
introducedFor
Indicates that one entity was presented or brought to the attention of another entity for a specific purpose or role.
-
D.
introducedModelFamily
Indicates that an entity (such as a person or organization) is responsible for first presenting or launching a particular model family.
-
E.
modelYears
chosen
Indicates the association between a product (often a vehicle or device) and the specific calendar years in which that model version was produced or marketed.
- 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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abcd0e42248190ada33b84d75caa64 |
completed | March 7, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69abc589295c819092989820c2b4e9d8 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:48 p.m.