Triple
T31957326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joe Toy |
E815940
|
entity |
| Predicate | storyResolutionInvolves |
P92023
|
FINISHED |
| Object | reconciliation with his father |
—
|
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: reconciliation with his father | Statement: [Joe Toy, storyResolutionInvolves, reconciliation with his father]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: storyResolutionInvolves Context triple: [Joe Toy, storyResolutionInvolves, reconciliation with his father]
-
A.
resolutionInStory
chosen
Indicates the part of a narrative where the central conflicts are resolved and the story’s outcomes are finalized.
-
B.
concludesStoryOf
Indicates that one entity brings the narrative or storyline of another entity to an end.
-
C.
involvedResolution
Indicates that an entity participated in or contributed to the process of resolving a particular issue, conflict, or problem.
-
D.
resolutionIdea
Indicates a proposed method, plan, or approach intended to resolve or address a particular issue, conflict, or problem.
-
E.
resolvedByCharacter
Indicates that a particular issue, conflict, or problem is brought to a conclusion or solved through the actions or decisions of a specific character.
- 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_69f348f4ec708190abbb2a7c3ed58844 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6f8565134819096aac0175f924a9f |
completed | May 3, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f6f65fd1d08190b88e5e68ba268500 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 12:08 a.m.