Triple
T11431169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | High Time |
E270882
|
entity |
| Predicate | mainCharacterOccupationBeforeCollege |
P28984
|
FINISHED |
| Object | restaurateur |
—
|
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: restaurateur | Statement: [High Time, mainCharacterOccupationBeforeCollege, restaurateur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCharacterOccupationBeforeCollege Context triple: [High Time, mainCharacterOccupationBeforeCollege, restaurateur]
-
A.
earlierOccupation
chosen
Indicates that one occupation held by an entity occurred before another occupation in that entity’s work history.
-
B.
characterFormerOccupation
Indicates that a character previously held a specific occupation but no longer does.
-
C.
hasOccupationDuringStory
Indicates that an entity holds or performs a particular occupation or job role during the time span covered by the story.
-
D.
plannedCareer
Indicates that an individual has chosen and intends to pursue a specific career path.
-
E.
studCareerBegan
Indicates that a student's professional or academic career started at a specified time or institution.
- 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_69d6aadeef688190874bcecd88b3dd9b |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d806c30d788190b0c939b33de89277 |
completed | April 9, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69d7e71436f88190ac7e45a04ea5c987 |
completed | April 9, 2026, 5:51 p.m. |
Created at: April 8, 2026, 9:35 p.m.