Triple
T9507366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ion Țuculescu |
E229301
|
entity |
| Predicate | hasDualCareer |
P88453
|
FINISHED |
| Object | science and art |
—
|
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: science and art | Statement: [Ion Țuculescu, hasDualCareer, science and art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDualCareer Context triple: [Ion Țuculescu, hasDualCareer, science and art]
-
A.
careerDoubles
Indicates the total number of doubles a person has achieved over the course of their entire career.
-
B.
hasCareerService
Indicates that an entity provides or is associated with a career-related support or advisory service for another entity.
-
C.
laterCareerWorkOf
Indicates that one work represents a creator’s later career output in relation to another work or to their overall body of work.
-
D.
hasCareerTrack
Indicates that an entity is associated with or follows a particular career path or professional progression.
-
E.
spouseOccupation
Indicates that one person’s spouse has a particular job, profession, or occupation.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98543b1881908b537abdc1d2f9c0 |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca567ca448190bf4bcce8ce7dd54f |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca89d0f0c8190b4528990fe708fca |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:57 p.m.