Triple
T28667008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Professor George Gammell Angell |
E725609
|
entity |
| Predicate | documentTypeAssociated |
P19006
|
FINISHED |
| Object | Angell papers |
—
|
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: Angell papers | Statement: [Professor George Gammell Angell, documentTypeAssociated, Angell papers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: documentTypeAssociated Context triple: [Professor George Gammell Angell, documentTypeAssociated, Angell papers]
-
A.
documentTypeUsed
Indicates that a particular type or category of document is employed or applied in a given context or activity.
-
B.
documentationType
chosen
Indicates the specific category or kind of documentation associated with or required for an entity or process.
-
C.
documentTypeIncluded
Indicates that a particular document type is contained within, or is part of, a specified set or collection of document types.
-
D.
documentTypeContext
Indicates the contextual relationship between a document and its specific type or classification within a given setting or usage scenario.
-
E.
documentsTypeOfStructure
Indicates that an entity records or specifies the particular type or classification of a structure.
- 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_69f01d85be388190b669a0e401e2f2c4 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f67c9fe7b48190b79b4041357edb49 |
completed | May 2, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 28, 2026, 5:01 a.m.