Triple
T25551012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Landgrave of Hesse |
E640438
|
entity |
| Predicate | subdivisionsLater |
P747
|
FINISHED |
| Object | Landgrave of Hesse-Kassel |
—
|
NE NERFINISHED |
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: Landgrave of Hesse-Kassel | Statement: [Landgrave of Hesse, subdivisionsLater, Landgrave of Hesse-Kassel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subdivisionsLater Context triple: [Landgrave of Hesse, subdivisionsLater, Landgrave of Hesse-Kassel]
-
A.
subdividedBy
Indicates that something is divided into smaller parts or sections by another entity or criterion.
-
B.
hasSubdivision
chosen
Indicates that one entity is divided into and contains another entity as one of its constituent parts or administrative units.
-
C.
traditionalSubdivisionOf
Indicates that one entity is a historically or culturally recognized sub-unit or component region of another, according to traditional (rather than strictly modern administrative) divisions.
-
D.
introducedSubdivision
Indicates that one entity created or formally established a new subdivision or sub-unit within another entity or structure.
-
E.
collectionSubdivision
Indicates that one collection is a constituent part, section, or subdivision of a larger collection.
- 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_69e75dc101a881909fd33b02174e9768 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 21, 2026, 3:36 p.m.