Triple
T2749296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert G. Heft |
E60944
|
entity |
| Predicate | reasonForDesign |
P41372
|
FINISHED |
| Object | addition of Alaska and Hawaii as U.S. states |
—
|
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: addition of Alaska and Hawaii as U.S. states | Statement: [Robert G. Heft, reasonForDesign, addition of Alaska and Hawaii as U.S. states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reasonForDesign Context triple: [Robert G. Heft, reasonForDesign, addition of Alaska and Hawaii as U.S. states]
-
A.
reasonForUse
Indicates that one entity specifies the justification, purpose, or motivation for using another entity.
-
B.
reasonForRedesign
Indicates the underlying cause, motivation, or justification for performing a redesign.
-
C.
reasonForCreation
Indicates that one entity was created for the purpose, cause, or motivation specified by another entity.
-
D.
designUse
Indicates that one entity is used as a design basis, purpose, or intended functional use for another entity.
-
E.
selectionReason
Indicates the reason or justification for choosing or selecting one entity over alternatives.
- F. None of above. chosen
Provenance (4 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_69ab4b79846081909096725374d65ce9 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abdb52b1d48190b6ab511cc8834a14 |
completed | March 7, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69abd829f1e88190aab1d54f87c69714 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd8dd05c48190b4f90031642c4091 |
completed | March 7, 2026, 7:50 a.m. |
Created at: March 6, 2026, 9:56 p.m.