Triple
T27226966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M‘Arthur |
E682040
|
entity |
| Predicate | oftenStandardizedTo |
P114275
|
FINISHED |
| Object | MacArthur |
—
|
NE NERFINISHED |
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: MacArthur | Statement: [M‘Arthur, oftenStandardizedTo, MacArthur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenStandardizedTo Context triple: [M‘Arthur, oftenStandardizedTo, MacArthur]
-
A.
oftenNormalizedTo
chosen
Indicates that one entity is frequently converted, mapped, or standardized into the form or representation of another entity.
-
B.
standardizedIn
Indicates that something has been formally defined, regulated, or made uniform within a particular standard, framework, or jurisdiction.
-
C.
standardizedBy
Indicates that one entity defines, regulates, or formalizes the standards or specifications by which another entity is created, measured, or operated.
-
D.
standardizedFor
Indicates that something has been adjusted or converted to conform to a common standard, format, or reference so it can be consistently compared or used.
-
E.
previouslyStandardizedAs
Indicates that an entity was formerly standardized under a different name, code, or specification than the one it currently has.
- 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_69eefacdad7881908b7bca61c90a1a1e |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 27, 2026, 9:44 a.m.