Triple
T19867121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Normandy Format |
E477418
|
entity |
| Predicate | involvesLevel |
P82125
|
FINISHED |
| Object | heads of state and government |
—
|
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: heads of state and government | Statement: [Normandy Format, involvesLevel, heads of state and government]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesLevel Context triple: [Normandy Format, involvesLevel, heads of state and government]
-
A.
involves
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
B.
typeOfInvolvement
chosen
Indicates the specific role, capacity, or manner in which one entity is involved with or participates in another entity or activity.
-
C.
levels
Indicates that one entity adjusts, equalizes, or smooths out the height, intensity, or degree of another entity.
-
D.
affectedLevel
Indicates the degree or extent to which one entity is impacted or influenced by another entity or event.
-
E.
exportLevel
Indicates the degree or extent to which something is produced in one place and sent out or made available to other places or markets.
- 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_69d8e51e7d948190aedbcd6c30361c39 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e658a0a7288190a82b85e3ae056d6b |
completed | April 20, 2026, 4:47 p.m. |
| PD | Predicate disambiguation | batch_69e537e8c4e481909fe95d795b4864e7 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:51 p.m.