Triple
T26332354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LU |
E662420
|
entity |
| Predicate | associatedWithDistrictFreeCity |
P152090
|
FINISHED |
| Object | Ludwigshafen am Rhein |
—
|
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: Ludwigshafen am Rhein | Statement: [LU, associatedWithDistrictFreeCity, Ludwigshafen am Rhein]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithDistrictFreeCity Context triple: [LU, associatedWithDistrictFreeCity, Ludwigshafen am Rhein]
-
A.
belongsToDistrictLevelCity
Indicates that an entity is administratively part of, or falls under the jurisdiction of, a specific district-level city.
-
B.
hasCityDistrictAlong
Indicates that a city district is located along or adjacent to a specified linear feature, such as a road, river, or coastline.
-
C.
hasCityDistrictCode
Indicates that a city district is associated with a specific identifying code.
-
D.
targetCityDistrict
Indicates that one entity is a specific city district that serves as the target or destination in relation to another entity.
-
E.
hasRelatedDistrict
chosen
Indicates that one entity is associated with, linked to, or falls within the scope of a particular district.
- 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_69ee812f32748190871d970c4e2a8ddf |
completed | April 26, 2026, 9:18 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 26, 2026, 10:34 p.m.