Triple
T23162522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rostock-Land |
E578623
|
entity |
| Predicate | hadAdministrativeStatus |
P71309
|
FINISHED |
| Object | Landkreis |
—
|
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: Landkreis | Statement: [Rostock-Land, hadAdministrativeStatus, Landkreis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadAdministrativeStatus Context triple: [Rostock-Land, hadAdministrativeStatus, Landkreis]
-
A.
hasAdministrativeStatusSince
Indicates that an entity has held a particular administrative status continuously from a specified point in time onward.
-
B.
administrativeStatusOfEntityRepresented
chosen
Indicates the current administrative or operational status assigned to the entity that is being represented.
-
C.
hadSpecialStatusIn
Indicates that an entity possessed a particular special, exceptional, or non-standard status within a specified context or time period.
-
D.
formerAdministrativeStatus
Indicates that an entity previously held, but no longer holds, a particular administrative status or role.
-
E.
hadAutomaticQualifierStatus
Indicates that an entity possessed an automatic qualification status, meaning it was deemed qualified without needing to undergo the usual qualifying process.
- 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_69e245fc75348190a0288401044c8af8 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18f019cd881908e3c68d99454da2a |
completed | April 29, 2026, 4:54 a.m. |
| PD | Predicate disambiguation | batch_69ef89ff76808190808ee4ad9dea776b |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:02 p.m.