Triple
T38394794
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Elizabeth Bennet and Fitzwilliam Darcy |
E900725
|
entity |
| Predicate | resolutionMeans |
P19705
|
FINISHED |
| Object | self-reflection |
—
|
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: self-reflection | Statement: [Elizabeth Bennet and Fitzwilliam Darcy, resolutionMeans, self-reflection]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resolutionMeans Context triple: [Elizabeth Bennet and Fitzwilliam Darcy, resolutionMeans, self-reflection]
-
A.
resolutionType
Indicates the specific manner or category by which an issue, event, or conflict is resolved or brought to a conclusion.
-
B.
resolution
Indicates the act of formally deciding, settling, or expressing a determined stance on an issue, often through an official decision or statement.
-
C.
resolutionMechanism
chosen
Indicates the method, process, or system used to resolve a conflict, issue, or discrepancy between entities.
-
D.
resolutionLeadsTo
Indicates that achieving a particular resolution or decision directly brings about or causes a subsequent outcome or state.
-
E.
resolutionMethod
Indicates the specific approach, technique, or process used to resolve a problem, conflict, or issue.
- 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_69f76e6071a081909eea7a670d21420c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fcd1499e2c81909bafd84dc4810f45 |
completed | May 7, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69fcccf024ec819086383ffbb6cfc036 |
completed | May 7, 2026, 5:33 p.m. |
Created at: May 3, 2026, 4:31 p.m.