Triple
T4571976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jürgen Stroop |
E123051
|
entity |
| Predicate | memberOf |
P10
|
FINISHED |
| Object | SS |
E1506
|
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: SS | Statement: [Jürgen Stroop, memberOf, SS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SS Context triple: [Jürgen Stroop, memberOf, SS]
-
A.
SS
chosen
The SS was a paramilitary organization of Nazi Germany that became one of the principal instruments of terror, repression, and mass murder, including the systematic genocide of Jews and other targeted groups during World War II.
-
B.
SS
SS is the IATA airline designator used to identify Corsair International flights in global aviation systems.
-
C.
SS
SS is the UK postcode area covering Southend-on-Sea and surrounding parts of Essex in eastern England.
-
D.
SS
The SS is a high-performance "Super Sport" trim level of the Chevrolet Camaro, featuring more powerful engines and sport-tuned components compared to standard models.
-
E.
SS
SS is a post-nominal abbreviation used by recipients of the U.S. military’s Silver Star Medal, one of the nation’s highest awards for valor in combat.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c711408190a2b096daf57e6eac |
completed | March 20, 2026, 2:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdd3cf5e10819099b2927c6f571673 |
completed | March 20, 2026, 11:10 p.m. |
Created at: March 20, 2026, 1:10 p.m.