Triple
T31096537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MTK |
E792544
|
entity |
| Predicate | startLettersOfDistrictName |
P198920
|
FINISHED |
| Object | Main-Taunus-Kreis |
—
|
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: Main-Taunus-Kreis | Statement: [MTK, startLettersOfDistrictName, Main-Taunus-Kreis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startLettersOfDistrictName Context triple: [MTK, startLettersOfDistrictName, Main-Taunus-Kreis]
-
A.
startPointAsUrbanDistrict
Indicates that the starting point of something (e.g., a route, event, or process) is located within an urban district.
-
B.
targetCityDistrict
Indicates that one entity is a specific city district that serves as the target or destination in relation to another entity.
-
C.
hasDistrictPart
Indicates that one administrative or geographic entity includes another entity as a district-level subdivision or component.
-
D.
currentNameOfDistrictAdministered
Indicates that the specified name is the present official name of the district that is (or was) administered in a given administrative context.
-
E.
governmentDistrict
Indicates that a government entity has jurisdiction over or is administratively associated with a specific district.
- F. None of above. chosen
Provenance (4 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_69f224cf157c81909e2d2bd88c9282c3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69ff14d596e88190be5263b7f96a96cd |
completed | May 9, 2026, 11:04 a.m. |
| PD | Predicate disambiguation | batch_69ff13f0208081909369aeb3b77a6b1f |
completed | May 9, 2026, 11:01 a.m. |
| PDg | Predicate description generation | batch_69ff14d4dfc48190bc9fba2384988a98 |
completed | May 9, 2026, 11:04 a.m. |
Created at: April 29, 2026, 9:03 p.m.