Triple
T12239023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Hohman |
E291677
|
entity |
| Predicate | hasEmployerTypeExperience |
P22183
|
FINISHED |
| Object | public company |
—
|
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: public company | Statement: [Robert Hohman, hasEmployerTypeExperience, public company]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmployerTypeExperience Context triple: [Robert Hohman, hasEmployerTypeExperience, public company]
-
A.
experienceType
Indicates the specific kind or category of experience associated with an entity or event.
-
B.
typeOfExperience
chosen
Indicates that one entity specifies the category or nature of an experience associated with another entity.
-
C.
hasGlobalExperience
Indicates that an entity possesses experience gained from working, operating, or engaging across multiple countries or international contexts.
-
D.
hasWorkedIn
Indicates that a person has been employed or has performed work within a particular organization, location, or domain for some period of time.
-
E.
hasMajorEmployerHistory
Indicates that an entity has a documented history of employment with a major or significant employer.
- 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_69d6ab67950c8190be08450a06228c4b |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d924a3973c8190a882046963b320fb |
completed | April 10, 2026, 4:26 p.m. |
| PD | Predicate disambiguation | batch_69d91c41bcbc81909782f4e3c571b218 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:51 p.m.