Triple
T32164194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julia Roberts as Julianne Potter |
E821511
|
entity |
| Predicate | firstMeetsMichaelBackstory |
P206204
|
FINISHED |
| Object | inCollege |
—
|
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: inCollege | Statement: [Julia Roberts as Julianne Potter, firstMeetsMichaelBackstory, inCollege]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMeetsMichaelBackstory Context triple: [Julia Roberts as Julianne Potter, firstMeetsMichaelBackstory, inCollege]
-
A.
firstMeets
Indicates that one entity encounters or comes into contact with another entity for the first time.
-
B.
firstMeetingDescription
Indicates a textual description of what happened or was communicated during the first meeting between the involved entities.
-
C.
firstMeetingSeason
Indicates the season of the year during which two entities first met.
-
D.
firstAppearanceAsMichaelHolt
Indicates the work or context in which an entity is first presented or identified specifically as Michael Holt.
-
E.
firstMeetingPlace
Indicates the location where two or more entities met each other for the very first time.
- 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_69f3490699a48190bbef96b198e8fade |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379eaa540819095a1c5d9f3513f9b |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 12:33 a.m.