Triple
T25027833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Israeli law |
E626756
|
entity |
| Predicate | codifiesArea |
P157912
|
FINISHED |
| Object | labor law |
—
|
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: labor law | Statement: [Israeli law, codifiesArea, labor law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codifiesArea Context triple: [Israeli law, codifiesArea, labor law]
-
A.
codifiesArea
chosen
Indicates that something formally defines or specifies the rules, structure, or characteristics of a particular area or domain.
-
B.
regulatesArea
Indicates that one entity exercises control or governance over the spatial extent, scope, or domain of another entity.
-
C.
codifiedIn
Indicates that something is formally recorded, defined, or established within a specific document, code, or legal/institutional text.
-
D.
regulatedArea
Indicates that an area is subject to specific rules, controls, or restrictions imposed by an authority.
-
E.
codifiedThrough
Indicates that something is formally established, expressed, or made authoritative by means of a specific codification process, document, or legal/institutional mechanism.
- 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_69e2ff28ee3881909c626af002457a4a |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f48b9b687881908fd87a2f5fa0b1e7 |
completed | May 1, 2026, 11:16 a.m. |
| PD | Predicate disambiguation | batch_69f48060597c8190a4414e4e4fcb1fec |
completed | May 1, 2026, 10:28 a.m. |
Created at: April 18, 2026, 6:07 a.m.