Triple
T797301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo Szilard |
E17050
|
entity |
| Predicate | laterCareer |
P19158
|
FINISHED |
| Object | molecular biologist at the Salk Institute for Biological Studies |
—
|
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: molecular biologist at the Salk Institute for Biological Studies | Statement: [Leo Szilard, laterCareer, molecular biologist at the Salk Institute for Biological Studies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterCareer Context triple: [Leo Szilard, laterCareer, molecular biologist at the Salk Institute for Biological Studies]
-
A.
careerStart
Indicates the point in time when an entity begins its professional career or main occupational activity.
-
B.
describesCareerOf
Indicates that one entity provides a description or characterization of the professional career of another entity.
-
C.
careerImpact
Indicates how one entity influences or changes another entity’s professional trajectory, opportunities, or outcomes.
-
D.
launchedCareerOf
Indicates that one entity’s actions, support, or involvement initiated or significantly advanced another entity’s professional career.
-
E.
careerOPS
Indicates a relationship where an entity’s career on-base plus slugging (OPS) statistic is recorded or associated with that entity.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7b342888190a344fe81a2c9f33c |
completed | March 1, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69a4a5122a008190b0c621b7bc588d41 |
completed | March 1, 2026, 8:44 p.m. |
| PDg | Predicate description generation | batch_69a4a5bed20c81909ecc28bf42594e72 |
completed | March 1, 2026, 8:46 p.m. |
Created at: March 1, 2026, 7:38 p.m.