Triple
T3755687
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wine Bar George |
E82040
|
entity |
| Predicate | hasBeverageProgram |
P50763
|
FINISHED |
| Object | curated wine list |
—
|
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: curated wine list | Statement: [Wine Bar George, hasBeverageProgram, curated wine list]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBeverageProgram Context triple: [Wine Bar George, hasBeverageProgram, curated wine list]
-
A.
hasCoopPrograms
Indicates that an entity offers or participates in cooperative education programs in partnership with other organizations or institutions.
-
B.
hasMembershipProgram
Indicates that an entity offers or participates in a structured membership program, typically providing special access, benefits, or services to enrolled members.
-
C.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
-
D.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
E.
establishedProgram
Indicates that an entity has created and put into operation a formal program that is now in an active, ongoing state.
- 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_69ad8b1db40081908b61ffa6b78afd4d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb96dd908190b787b112ecd519df |
completed | March 8, 2026, 7:18 p.m. |
| PD | Predicate disambiguation | batch_69adc04c851c8190ae5eaebf36df539b |
completed | March 8, 2026, 6:30 p.m. |
| PDg | Predicate description generation | batch_69adc0fe3e3c8190bd886c7745c172a0 |
completed | March 8, 2026, 6:33 p.m. |
Created at: March 8, 2026, 3:35 p.m.