Triple
T3099319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace After Meals |
E64675
|
entity |
| Predicate | oftenIntroducedBy |
P45921
|
FINISHED |
| Object | Zimun |
—
|
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: Zimun | Statement: [Grace After Meals, oftenIntroducedBy, Zimun]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenIntroducedBy Context triple: [Grace After Meals, oftenIntroducedBy, Zimun]
-
A.
introduced
Indicates that one entity caused another entity to become known, presented, or brought into use for the first time to a person, group, or context.
-
B.
introducedByOrganization
Indicates that an entity was brought into existence, presented, or launched by a specific organization.
-
C.
introducedTo
Indicates that one entity caused or facilitated a first meeting or formal presentation between another entity and a third party.
-
D.
introducedAlongWith
Indicates that one entity was introduced or presented at the same time as another entity, as part of a joint or concurrent introduction.
-
E.
introducedByCharacter
Indicates that one character is responsible for presenting, bringing into the story, or otherwise causing another entity to be first revealed or made known.
- 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_69ad857dc98481909e585dc3372e3ed5 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada269a9188190aada5b3799d4dfd7 |
completed | March 8, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69ad9df06ed88190809f0683122caa5a |
completed | March 8, 2026, 4:04 p.m. |
| PDg | Predicate description generation | batch_69ada0f6fef48190b13898be383a246b |
completed | March 8, 2026, 4:16 p.m. |
Created at: March 8, 2026, 3:03 p.m.