Triple
T19980643
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sonnet 29 |
E493806
|
entity |
| Predicate | resolutionCause |
P138150
|
FINISHED |
| Object | remembrance of a beloved friend |
—
|
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: remembrance of a beloved friend | Statement: [Sonnet 29, resolutionCause, remembrance of a beloved friend]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resolutionCause Context triple: [Sonnet 29, resolutionCause, remembrance of a beloved friend]
-
A.
resolutionType
Indicates the specific manner or category by which an issue, event, or conflict is resolved or brought to a conclusion.
-
B.
resolutionEvent
Indicates an event or action through which a previously existing issue, conflict, or problem is brought to a conclusion or resolved.
-
C.
resolution
Indicates the act of formally deciding, settling, or expressing a determined stance on an issue, often through an official decision or statement.
-
D.
resolutionLeadsTo
Indicates that achieving a particular resolution or decision directly brings about or causes a subsequent outcome or state.
-
E.
resolutionIdea
Indicates a proposed method, plan, or approach intended to resolve or address a particular issue, conflict, or problem.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d12d968819081e315ec4585cd9f |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c42c688190a22f4d31ec692377 |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 11, 2026, 3:28 p.m.