Triple
T8051076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BSE |
E187673
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | BSE |
E268089
|
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: BSE | Statement: [BSE, abbreviation, BSE]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BSE Context triple: [BSE, abbreviation, BSE]
-
A.
BSE
BSE is the abbreviation for Britain Stronger in Europe, the main cross-party campaign that advocated for the United Kingdom to remain in the European Union during the 2016 EU referendum.
-
B.
BSE
chosen
BSE is one of Asia’s oldest and largest stock exchanges, based in Mumbai, India, and a key hub for trading in Indian securities.
-
C.
BSE Global
BSE Global is the sports and entertainment company that owns and operates the Brooklyn Nets and related properties.
-
D.
Schmallenberg
Schmallenberg is a small town in the Hochsauerland district of North Rhine-Westphalia, Germany, known for its picturesque landscapes and tourism in the Sauerland region.
-
E.
Bové
Bové is the surname of Joseph Bové, a prominent 19th-century architect known for helping shape the neoclassical appearance of central Moscow.
- 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_69ca82b15e948190a62fd7af5218426a |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f799d1481909c91039941af0e34 |
completed | March 31, 2026, 3:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc571b737881909ae8eadcc7894223 |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 5:24 p.m.