Triple
T211036
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Society of Rheology |
E4717
|
entity |
| Predicate | hasDigitalObjectIdentifierPrefix |
P1285
|
FINISHED |
| Object | 10.1122 |
—
|
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: 10.1122 | Statement: [Society of Rheology, hasDigitalObjectIdentifierPrefix, 10.1122]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDigitalObjectIdentifierPrefix Context triple: [Society of Rheology, hasDigitalObjectIdentifierPrefix, 10.1122]
-
A.
hasIdentifierSystem
chosen
Indicates that an entity is associated with a particular system or scheme used to assign and manage its identifiers.
-
B.
hasDeweyDecimalClassification
Indicates that an item (such as a book or resource) is assigned a specific Dewey Decimal Classification number representing its subject area in a library system.
-
C.
hasDigitalArchive
Indicates that an entity maintains or is associated with a collection of materials stored in a digital archive.
-
D.
hasLccn
Indicates that an entity is associated with a specific Library of Congress Control Number (LCCN) as its unique identifier in the Library of Congress catalog.
-
E.
hasDigitalLibrary
Indicates that an entity maintains or provides access to a collection of digital resources or publications.
- 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_69a2575cb1dc8190a01ad332426dc339 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25d35aa288190966b6e15af1525cb |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b4f71b88190866c8262922ae204 |
completed | Feb. 28, 2026, 3:04 a.m. |
Created at: Feb. 28, 2026, 2:52 a.m.