Triple
T1132246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bastian Schweinsteiger |
E23057
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Bastian |
E56526
|
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: Bastian | Statement: [Bastian Schweinsteiger, givenName, Bastian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bastian Context triple: [Bastian Schweinsteiger, givenName, Bastian]
-
A.
Bastian
chosen
Bastian is a surname most prominently associated with Ed Bastian, the CEO of Delta Air Lines.
-
B.
Sebastian
Sebastian is a masculine given name of Latin origin, commonly used in many European and English-speaking countries.
-
C.
Bruno
Bruno is a masculine given name of Germanic origin, commonly used in various European and Latin American countries.
-
D.
Tobias
Tobias was a Native American man from the 17th-century Wampanoag community, known primarily through his familial connection to the Sakonnet leader Awashonks.
-
E.
Yann
Yann is the given name of Yann LeCun, a pioneering computer scientist known for his foundational work in deep learning and convolutional neural networks.
- 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_69a493ec75988190b63a11bafaec29b4 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4bbfcdf848190a2917d796ca84b74 |
completed | March 1, 2026, 10:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac59aa261881908c7ceedf710ee9c8 |
completed | March 7, 2026, 5 p.m. |
Created at: March 1, 2026, 7:44 p.m.