Triple
T9279246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Scott |
E223027
|
entity |
| Predicate | roleInMichaelScottPaperCompany |
P61558
|
FINISHED |
| Object | founder |
—
|
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: founder | Statement: [Michael Scott, roleInMichaelScottPaperCompany, founder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInMichaelScottPaperCompany Context triple: [Michael Scott, roleInMichaelScottPaperCompany, founder]
-
A.
cultRole
Indicates that an entity holds a specific role, position, or function within a cult or cult-like group.
-
B.
roleInRhyme
Indicates the specific function or part an entity plays within a rhyme, such as a character, object, or structural element of the rhyming text.
-
C.
officeItAbbreviatesRole
Indicates that an office title or designation serves as an abbreviation for a particular role or position.
-
D.
roleInText
Indicates that an entity participates in a text with a specific function or capacity (e.g., author, editor, character).
-
E.
hasFictionalStaffMember
chosen
Indicates that an entity includes or employs a staff member who is a fictional character.
- 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_69ca842123588190b3f2e1a69037d141 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd07cc79508190954defbef0d82a64 |
completed | April 1, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_69cc7a576ec88190bbb787eb82e2e539 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:34 p.m.