Triple
T9393813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Vronsky |
E226091
|
entity |
| Predicate | preWarLife |
P43088
|
FINISHED |
| Object | works in a steel mill with friends |
—
|
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: works in a steel mill with friends | Statement: [Michael Vronsky, preWarLife, works in a steel mill with friends]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preWarLife Context triple: [Michael Vronsky, preWarLife, works in a steel mill with friends]
-
A.
prewarActivity
Indicates activities, conditions, or behaviors that occurred or were carried out before a specific war or armed conflict.
-
B.
preWarCountry
Indicates that a country existed or held a particular status prior to a specified war or major armed conflict.
-
C.
prewarStatus
Indicates the condition, role, or circumstances of an entity as they existed before a specific war or armed conflict.
-
D.
preWarOccupation
chosen
Indicates the occupation or role a person held before a specific war or armed conflict.
-
E.
preWarCharacter
Indicates that a character existed or had a particular state or role prior to a specified war or conflict.
- 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_69ca842f7e3481908bf5bcf52e032dbd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd511150008190be04142e477e8bf1 |
completed | April 1, 2026, 5:08 p.m. |
| PD | Predicate disambiguation | batch_69cca545b2448190a4297312e39c21ac |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:45 p.m.