Triple
T146814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Art of the Deal |
E3347
|
entity |
| Predicate | hasOclcNumber |
P1214
|
FINISHED |
| Object | 15251613 |
—
|
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: 15251613 | Statement: [The Art of the Deal, hasOclcNumber, 15251613]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasOclcNumber Context triple: [The Art of the Deal, hasOclcNumber, 15251613]
-
A.
OCLC
chosen
Indicates that an entity is associated with an OCLC (Online Computer Library Center) control number or record identifier in a bibliographic or library cataloging context.
-
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.
hasLCClassification
Indicates that an entity is assigned a specific Library of Congress Classification code representing its subject or shelving category.
-
D.
hasDigitalArchive
Indicates that an entity maintains or is associated with a collection of materials stored in a digital archive.
-
E.
isbn
Indicates that a publication is associated with a specific International Standard Book Number (ISBN) that uniquely identifies it.
- 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_69a252868de4819080e21c9938bfe8b6 |
completed | Feb. 28, 2026, 2:27 a.m. |
| NER | Named-entity recognition | batch_69a258808ff08190a06b6206f635612b |
completed | Feb. 28, 2026, 2:52 a.m. |
| PD | Predicate disambiguation | batch_69a256580c2c8190beecca60ca8595f3 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.