Triple
T27566678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 32. Gün |
E695920
|
entity |
| Predicate | hasCoverageStyle |
P63754
|
FINISHED |
| Object | in-depth analysis |
—
|
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: in-depth analysis | Statement: [32. Gün, hasCoverageStyle, in-depth analysis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCoverageStyle Context triple: [32. Gün, hasCoverageStyle, in-depth analysis]
-
A.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
-
B.
knownForCoverageStyle
chosen
Indicates that an entity is recognized or distinguished by a particular style or manner of coverage (e.g., how it reports on or presents information or events).
-
C.
hasCoverageFocus
Indicates that one entity’s coverage, attention, or analysis is specifically focused on or directed toward another entity.
-
D.
hasStyle
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
E.
hasKeyCoverage
Indicates that one entity’s key or set of keys provides coverage, access, or applicability over another entity or domain.
- 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_69ef53891af88190a193c5e2a1dac9b1 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69ff17be6ad48190963206f2619b1b28 |
completed | May 9, 2026, 11:17 a.m. |
| PD | Predicate disambiguation | batch_69ff1724ba24819092c928fcbcb286ec |
completed | May 9, 2026, 11:14 a.m. |
Created at: April 27, 2026, 1:41 p.m.