Triple
T33623248
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgil Sollozzo |
E861328
|
entity |
| Predicate | meetsAtRestaurantWith |
P1220
|
FINISHED |
| Object | Michael Corleone |
—
|
NE NERFINISHED |
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: Michael Corleone | Statement: [Virgil Sollozzo, meetsAtRestaurantWith, Michael Corleone]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsAtRestaurantWith Context triple: [Virgil Sollozzo, meetsAtRestaurantWith, Michael Corleone]
-
A.
meetsVia
Indicates that two entities come into contact or interact with each other through a specified intermediary medium, channel, or mechanism.
-
B.
meets
chosen
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
C.
meetingPlaceOf
Indicates the location where a particular meeting or gathering takes place or is held for the referenced entities.
-
D.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
E.
rendezvousWith
Indicates that two or more entities meet or come together at an agreed place and time, often for a specific purpose.
- 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_69f34980fabc81909819228729a9ca84 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f81ea9388190bf58dad0672e7697 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:41 a.m.