Triple
T18107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wholly New Forms of Encyclopedias |
E357
|
entity |
| Predicate | contrastsWith |
P278
|
FINISHED |
| Object | traditional printed encyclopedias |
—
|
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: traditional printed encyclopedias | Statement: [Wholly New Forms of Encyclopedias, contrastsWith, traditional printed encyclopedias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contrastsWith Context triple: [Wholly New Forms of Encyclopedias, contrastsWith, traditional printed encyclopedias]
-
A.
complements
Indicates that one entity enhances, completes, or improves another by providing qualities or functions that fit well together.
-
B.
opposedBy
Indicates that one entity actively resists, disagrees with, or works against the actions, views, or position of another entity.
-
C.
isComparedTo
chosen
Indicates that one entity is evaluated or measured in relation to another to highlight similarities, differences, or relative qualities.
-
D.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
E.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
- 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_69a23d7ad88c8190bffe8ab091d86642 |
completed | Feb. 28, 2026, 12:57 a.m. |
| NER | Named-entity recognition | batch_69a242494a548190a5776fb6cad4d4af |
completed | Feb. 28, 2026, 1:18 a.m. |
| PD | Predicate disambiguation | batch_69a23fedf0fc8190ad99bd1da297b14d |
completed | Feb. 28, 2026, 1:07 a.m. |
Created at: Feb. 28, 2026, 1:02 a.m.