Triple
T65948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | March Meeting |
E1313
|
entity |
| Predicate | contributionType |
P1366
|
FINISHED |
| Object | oral presentations |
—
|
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: oral presentations | Statement: [March Meeting, contributionType, oral presentations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: contributionType Context triple: [March Meeting, contributionType, oral presentations]
-
A.
contributeTo
Indicates that one entity provides support, resources, or effort that helps bring about, enhance, or maintain another entity, outcome, or state.
-
B.
notableContribution
Indicates that an entity has made a significant, recognized contribution to another entity, field, work, or endeavor.
-
C.
typeOfSupport
Indicates the kind or category of assistance, help, or backing provided in a given context.
-
D.
sponsorType
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
-
E.
typeOfWork
chosen
Indicates the kind or category of work associated with or performed by an entity.
- 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a2516eda54819090f5c14384d4eab1 |
completed | Feb. 28, 2026, 2:22 a.m. |
| PD | Predicate disambiguation | batch_69a24ea5c140819080409a968c8d2ce8 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.