Triple
T9056311
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Froggie Went A-Courtin’ |
E217005
|
entity |
| Predicate | hasNarrativeOutcome |
P86129
|
FINISHED |
| Object | wedding feast |
—
|
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: wedding feast | Statement: [Froggie Went A-Courtin’, hasNarrativeOutcome, wedding feast]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNarrativeOutcome Context triple: [Froggie Went A-Courtin’, hasNarrativeOutcome, wedding feast]
-
A.
hasNarrative
Indicates that one entity contains, presents, or is associated with a story or narrative about another entity or subject.
-
B.
hasNarrativeRole
Indicates that an entity participates in a narrative with a specific functional role (e.g., protagonist, antagonist, narrator) relative to the story.
-
C.
containsNarrativeOf
Indicates that one entity includes or presents the story, account, or narrative content of another entity.
-
D.
hasCauseNarrative
Indicates that one entity provides a narrative or explanatory account of the cause or causal background of another entity or event.
-
E.
hasPartInNarrative
Indicates that one entity plays a role or participates as a component within the storyline or structure of another narrative 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_69ca83d4425481909a319dab847724ec |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc7a75d8e881909414d745ec054182 |
completed | April 1, 2026, 1:52 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee6d83c819095d8ed0779aa8511 |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5f4f1cb48190a025d1b3d8d7a790 |
completed | March 31, 2026, 11:57 p.m. |
Created at: March 30, 2026, 7:10 p.m.