Triple
T21382670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wiesloch |
E527400
|
entity |
| Predicate | hasNearbyCompanyHeadquarters |
P44325
|
FINISHED |
| Object | SAP SE in Walldorf |
—
|
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: SAP SE in Walldorf | Statement: [Wiesloch, hasNearbyCompanyHeadquarters, SAP SE in Walldorf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyCompanyHeadquarters Context triple: [Wiesloch, hasNearbyCompanyHeadquarters, SAP SE in Walldorf]
-
A.
hasMajorCompanyNearby
Indicates that a location or entity is situated close to at least one large or significant company.
-
B.
associatedWithCompanyHeadquarters
Indicates that an entity has a relationship or connection to the headquarters location of a specific company.
-
C.
isCompanyTownOf
Indicates that a town is economically and socially dominated or controlled by a particular company, typically through ownership of major housing, services, and employment.
-
D.
hasParentCompanyHeadquarters
Indicates that a company’s parent organization has its main headquarters located at a specified place.
-
E.
nearHeadquartersOf
chosen
Indicates that one entity is located geographically close to the headquarters of another entity.
- 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_69e0b51f363c8190944000ab5523b02b |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b0d1fa1c8190b3374e0bb3a971fc |
completed | April 22, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_69e6162bbfc88190a3e75859941b2638 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 5:12 p.m.