Triple
T6759368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Pacific Railway |
E154551
|
entity |
| Predicate | landGrantMileage |
P19614
|
FINISHED |
| Object | approximately 40 million acres |
—
|
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 40 million acres | Statement: [Northern Pacific Railway, landGrantMileage, approximately 40 million acres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landGrantMileage Context triple: [Northern Pacific Railway, landGrantMileage, approximately 40 million acres]
-
A.
landGrantField
Indicates that a specific field or parcel of land has been allocated or granted, typically by an authority, to a recipient under a land grant arrangement.
-
B.
landGrantLocation
Indicates the geographic place or area to which a particular land grant applies or in which it is situated.
-
C.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
-
D.
landGrantDesignation
Indicates that an institution has been formally designated as a land-grant institution under a land-grant program or legislation.
-
E.
hasNumberOfAcres
chosen
Indicates the specific quantity of land area, measured in acres, that is associated with an entity.
- 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_69c6880fd5808190be684854081e27dd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d327e37081909d576e6eff9eec97 |
completed | March 27, 2026, 6:57 p.m. |
| PD | Predicate disambiguation | batch_69c6d09227108190b253b91967831a85 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:12 p.m.