Triple
T15203039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BT |
E363313
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | BT Business |
E363311
|
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: BT Business | Statement: [BT, subsidiary, BT Business]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BT Business Context triple: [BT, subsidiary, BT Business]
-
A.
BT Business
chosen
BT Business is the business-focused division of BT Group that provides communications and IT services to corporate and public sector customers.
-
B.
Business Center
Business Center is a World Resources Institute program that engages companies to advance sustainable business practices and environmental responsibility.
-
C.
Business Link
Business Link was a UK government-funded advisory service that provided information and support to businesses, particularly small and medium-sized enterprises.
-
D.
Carrier Business
Carrier Business is Huawei’s telecommunications-focused division that provides network infrastructure, solutions, and services to mobile and fixed-line operators worldwide.
-
E.
BT
BT is the vehicle registration code used on license plates for the city and district of Bayreuth in Upper Franconia, Germany.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b693a48190a6230b7b52bc8cd3 |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fedd2dc6f08190a8f1612ac29a8654 |
completed | May 9, 2026, 7:07 a.m. |
Created at: April 10, 2026, 3:10 a.m.