Triple
T12436408
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jospin Government |
E297153
|
entity |
| Predicate | notableReformArea |
P88043
|
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: [Jospin Government, notableReformArea, labor law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableReformArea Context triple: [Jospin Government, notableReformArea, labor law]
-
A.
notableReform
Indicates that an entity is recognized for having initiated, led, or been central to a significant reform or transformative change in a system, policy, or institution.
-
B.
reformsArea
chosen
Indicates that an entity is responsible for changing, improving, or restructuring a particular area or domain.
-
C.
typeOfReforms
Indicates the specific kinds or categories of reforms associated with an entity or situation.
-
D.
relatedReforms
Indicates that one reform is connected or associated with another reform, typically through shared goals, content, or impact.
-
E.
reform
Indicates bringing about significant changes to an existing system, practice, or entity in order to improve or correct it.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94df948308190ace333230a4a3b38 |
completed | April 10, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_69d94d391c548190996a8c698357f273 |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:55 p.m.