Triple
T34795314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sir Clifford Chatterley |
E1003060
|
entity |
| Predicate | sexualRelationshipTo |
P181480
|
FINISHED |
| Object | impotent with his wife |
—
|
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: impotent with his wife | Statement: [Sir Clifford Chatterley, sexualRelationshipTo, impotent with his wife]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sexualRelationshipTo Context triple: [Sir Clifford Chatterley, sexualRelationshipTo, impotent with his wife]
-
A.
inRelationshipWith
Indicates that two entities are mutually involved in a defined personal, romantic, or partnership relationship with each other.
-
B.
worksInCloseRelationshipWith
Indicates a collaborative professional relationship in which two or more entities work together closely and interact frequently to achieve shared goals.
-
C.
spouseOrLover
Indicates a romantic partnership between two entities, whether formalized as a spouse or existing as a lover.
-
D.
haveRelationshipWith
Indicates that one entity is in some form of defined relationship or association with another entity.
-
E.
relationshipToSpouse
Indicates the specific familial or social role one person holds in relation to their spouse (e.g., husband, wife, partner).
- 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_69f76db543808190b188c6c86a91491b |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77ab085088190ace5734dcc9f1167 |
completed | May 3, 2026, 4:41 p.m. |
| PD | Predicate disambiguation | batch_69f7795b1abc8190823664d1caa94649 |
completed | May 3, 2026, 4:35 p.m. |
| PDg | Predicate description generation | batch_69f77a39135081908ae22d2a23b44e74 |
completed | May 3, 2026, 4:39 p.m. |
Created at: May 3, 2026, 3:59 p.m.