Triple
T22615718
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | beylerbey |
E558139
|
entity |
| Predicate | territorialUnitCalled |
P112037
|
FINISHED |
| Object | beylerbeylik |
—
|
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: beylerbeylik | Statement: [beylerbey, territorialUnitCalled, beylerbeylik]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territorialUnitCalled Context triple: [beylerbey, territorialUnitCalled, beylerbeylik]
-
A.
territoryCorrespondedTo
Indicates that one territory matched, aligned with, or was equivalent to another territory in scope, boundaries, or designation.
-
B.
missionTerritoryOf
Indicates that a specified territory is under the jurisdiction or scope of a particular mission.
-
C.
regionAlsoCalled
chosen
Indicates that a geographic or administrative region is known by an alternative name or alias.
-
D.
territorialLevel
Indicates the administrative or geographic tier at which something is defined, applied, or governed within a territorial hierarchy.
-
E.
territorialDesignation
Indicates that an entity is assigned, defined, or recognized in terms of a specific geographic or territorial area.
- 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_69e24545a8e08190bfa7482a2c725ff1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f167edec2481909c2f06607b3cb8f6 |
completed | April 29, 2026, 2:07 a.m. |
| PD | Predicate disambiguation | batch_69ee62855558819080da946c7b35a160 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:59 p.m.