Triple
T1000326
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Södertälje Municipality |
E21587
|
entity |
| Predicate | hasMajorEmployer |
P588
|
FINISHED |
| Object | Scania AB |
E37748
|
NE 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: Scania AB | Statement: [Södertälje Municipality, hasMajorEmployer, Scania AB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Scania AB Context triple: [Södertälje Municipality, hasMajorEmployer, Scania AB]
-
A.
Scania
chosen
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
-
B.
Volvo Cars
Volvo Cars is a Swedish automotive manufacturer known for its focus on safety, practical design, and premium vehicles.
-
C.
Saab AB
Saab AB is a Swedish aerospace and defense company known for developing military aircraft, advanced defense systems, and security solutions.
-
D.
Saab Automobile
Saab Automobile was a Swedish car manufacturer known for its innovative engineering, turbocharged engines, and distinctive, safety-focused designs.
-
E.
Saab Kockums
Saab Kockums is a Swedish shipyard and defense company best known for designing and building advanced submarines and naval vessels.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac2a1aab68819091537958818fce48 |
completed | March 7, 2026, 1:37 p.m. |
Created at: March 1, 2026, 7:41 p.m.