Triple
T646073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston and Maine Railroad |
E11243
|
entity |
| Predicate | primaryCommodityCarried |
P5941
|
FINISHED |
| Object | manufactured goods |
—
|
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: manufactured goods | Statement: [Boston and Maine Railroad, primaryCommodityCarried, manufactured goods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCommodityCarried Context triple: [Boston and Maine Railroad, primaryCommodityCarried, manufactured goods]
-
A.
mainCargo
chosen
Indicates that one entity serves as the primary or principal cargo carried or transported by another entity.
-
B.
commodity
Indicates that one entity is a tradable good or resource that is bought, sold, or exchanged in relation to another entity.
-
C.
primaryProduct
Indicates that one entity is the main or most important product associated with, produced by, or offered by another entity.
-
D.
majorCrop
Indicates that a particular crop is one of the primary or most important crops cultivated in a given area or context.
-
E.
usedInInternationalTrade
Indicates that something participates as a good, service, or instrument in commercial exchanges between different countries.
- 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_69a493266a2881909daf4c40f719dee8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49f1b24b08190897d8aedb877bd83 |
completed | March 1, 2026, 8:18 p.m. |
| PD | Predicate disambiguation | batch_69a49d0c0dcc8190849211d45489a5a7 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:36 p.m.