Triple
T34795388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Thomas and Lady Jane |
E1003062
|
entity |
| Predicate | isLessExplicitThan |
P181481
|
FINISHED |
| Object | Lady Chatterley’s Lover |
—
|
NE NERFINISHED |
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: Lady Chatterley’s Lover | Statement: [John Thomas and Lady Jane, isLessExplicitThan, Lady Chatterley’s Lover]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLessExplicitThan Context triple: [John Thomas and Lady Jane, isLessExplicitThan, Lady Chatterley’s Lover]
-
A.
isExplicit
Indicates that something is stated clearly and directly, leaving no room for ambiguity or implied interpretation.
-
B.
isMoreSpecificThan
Indicates that one concept represents a narrower, more detailed, or more constrained case of another concept.
-
C.
isLessFormalThan
Indicates that one entity has a lower level of formality or is more casual in style, tone, or usage compared to another entity.
-
D.
isLessAccessibleThan
Indicates that one entity can be reached, used, or understood with more difficulty or under more constraints than another entity.
-
E.
isLessStandardizedThan
Indicates that one entity follows fewer or less rigid standards, norms, or formalized procedures than another entity.
- 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.