Triple
T670859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Observateur |
E12966
|
entity |
| Predicate | editorialOrientation |
P8702
|
FINISHED |
| Object | politically engaged |
—
|
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: politically engaged | Statement: [L’Observateur, editorialOrientation, politically engaged]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: editorialOrientation Context triple: [L’Observateur, editorialOrientation, politically engaged]
-
A.
editorialStandard
Indicates that one entity defines, follows, or enforces a particular set of editorial rules, guidelines, or quality criteria in relation to another entity or content.
-
B.
hasEditorialFocus
Indicates that an entity (such as a publication or section) is primarily concerned with or oriented around a particular editorial topic, theme, or subject area.
-
C.
editedBy
Indicates that one entity has revised, modified, or otherwise made editorial changes to another entity.
-
D.
editorialStance
chosen
Indicates the position, viewpoint, or bias an editor or publication adopts toward a subject, issue, or entity.
-
E.
edition
Indicates that one entity is a specific version, issue, or release of another (typically a work such as a book, journal, or software).
- 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4a1b3682c8190a9b9a454480c3446 |
completed | March 1, 2026, 8:29 p.m. |
| PD | Predicate disambiguation | batch_69a49d1a16c48190af89e3b078a4957e |
completed | March 1, 2026, 8:10 p.m. |
Created at: March 1, 2026, 7:36 p.m.