Triple
T7407763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Gadsden |
E170918
|
entity |
| Predicate | purposeOfPurchase |
P79
|
FINISHED |
| Object | facilitate a southern transcontinental railroad route |
—
|
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: facilitate a southern transcontinental railroad route | Statement: [James Gadsden, purposeOfPurchase, facilitate a southern transcontinental railroad route]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: purposeOfPurchase Context triple: [James Gadsden, purposeOfPurchase, facilitate a southern transcontinental railroad route]
-
A.
orderPurpose
Indicates that an order is placed with the specific purpose or intended use of the ordered item or service.
-
B.
typicalLoanPurpose
Indicates the usual or intended purpose for which a loan is taken or used.
-
C.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
D.
categoryIUsedFor
Indicates that one entity is used as a category or classification label for another entity.
-
E.
purpose
chosen
Indicates that one entity exists, is done, or is used in order to achieve, support, or serve the goal, function, or intended outcome of another 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_69c68a6010108190925e5284de022660 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f298f2388190afc944c9bc78749a |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f0323b2c819098ab72c33e6d8534 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:10 p.m.