Triple
T16857979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stig Björkman |
E409836
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Stig |
E869244
|
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: Stig | Statement: [Stig Björkman, givenName, Stig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stig Context triple: [Stig Björkman, givenName, Stig]
-
A.
Stig
chosen
Stig is a Scandinavian male given name commonly used in Sweden and other Nordic countries.
-
B.
Stig
Stig is a historical region in eastern Serbia known for its fertile plains and agricultural significance.
-
C.
Sten
Sten is a Scandinavian male given name of Old Norse origin, commonly associated with Sweden and meaning "stone."
-
D.
Black Stig
Black Stig is the original, black-suited incarnation of The Stig, the anonymous racing driver character from the BBC motoring show Top Gear.
-
E.
Stößen
Stößen is a small town in the German state of Saxony-Anhalt that forms part of the broader Leipzig metropolitan area.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37ef4748190b149d98fc0ab4205 |
completed | April 18, 2026, 4:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00bb25300c8190a352037c21c244bd |
completed | May 10, 2026, 5:06 p.m. |
Created at: April 10, 2026, 5:24 a.m.