Triple
T12774666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Chatterley's Lover was subject to obscenity trials |
E305335
|
entity |
| Predicate | hasRelatedField |
P106841
|
FINISHED |
| Object | literary studies |
—
|
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: literary studies | Statement: [Lady Chatterley's Lover was subject to obscenity trials, hasRelatedField, literary studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelatedField Context triple: [Lady Chatterley's Lover was subject to obscenity trials, hasRelatedField, literary studies]
-
A.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
B.
hasRelatedResult
Indicates that one entity has an associated outcome, effect, or result that is meaningfully connected to it.
-
C.
hasFieldName
Indicates that one entity is associated with, or identified by, a specific field name in a data structure or schema.
-
D.
hasBaseField
Indicates that one entity serves as the foundational or underlying field structure upon which another entity is defined or constructed.
-
E.
hasFieldContribution
Indicates that an entity has made a contribution or provided input within a particular field, domain, or area of activity.
- F. None of above. chosen
Provenance (4 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_69d7bdf2b43c819098ae5aa68e61ea58 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96df6b3c88190b0bbe70de8ddcbf3 |
completed | April 10, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69d9640ba0688190973e4e7ec8d4a8e0 |
completed | April 10, 2026, 8:56 p.m. |
| PDg | Predicate description generation | batch_69d96d87078c819083ea724238992204 |
completed | April 10, 2026, 9:37 p.m. |
Created at: April 9, 2026, 5:29 p.m.