Triple
T8607877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North American truck market |
E203847
|
entity |
| Predicate | majorApplication |
P13668
|
FINISHED |
| Object | freight transportation |
—
|
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: freight transportation | Statement: [North American truck market, majorApplication, freight transportation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorApplication Context triple: [North American truck market, majorApplication, freight transportation]
-
A.
majorActivity
Indicates that the related entity performs, participates in, or is primarily associated with a main or most significant activity.
-
B.
majorUse
chosen
Indicates that something serves as the primary or most significant use or application of an entity.
-
C.
majorFor
Indicates that an academic program, field of study, or specialization is the primary major associated with a particular student or degree.
-
D.
majorSee
Indicates that one entity serves as the primary or most important location where another entity is based, operates, or is centered.
-
E.
majorContext
Indicates that one entity serves as the primary or most significant contextual framework within which the other entity is understood or interpreted.
- 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_69ca832c23e4819095a9f3eea4a21828 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cc46ec301881908ce148a3f07069fe |
completed | March 31, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69cc454eb2908190acf0e4336bc67e7b |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:25 p.m.