Triple
T31248723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | לבן הארמי |
E796756
|
entity |
| Predicate | משך_שנות_עבודה |
P19680
|
FINISHED |
| Object | שבע_שנים_עבור_רחל |
—
|
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: שבע_שנים_עבור_רחל | Statement: [לבן הארמי, משך_שנות_עבודה, שבע_שנים_עבור_רחל]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: משך_שנות_עבודה Context triple: [לבן הארמי, משך_שנות_עבודה, שבע_שנים_עבור_רחל]
-
A.
workYear
Indicates the specific year or span of years during which an entity (such as a person or organization) was engaged in work or employment.
-
B.
timeInCareer
Indicates the point or duration within an entity’s professional or occupational trajectory at which a related event, status, or condition occurs.
-
C.
occupationDuration
chosen
Indicates the length of time an entity holds or has held a particular occupation or role.
-
D.
hasExperienceOf
Indicates that one entity has undergone, encountered, or lived through a particular event, situation, or activity associated with another entity.
-
E.
premiereWorkYear
Indicates the year in which a work (such as a performance, film, or composition) was first premiered or publicly presented.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:11 p.m.