Triple
T55782
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IBM |
E1102
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | IBM Deutschland |
E1102
|
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: IBM Deutschland | Statement: [IBM, subsidiary, IBM Deutschland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: IBM Deutschland Context triple: [IBM, subsidiary, IBM Deutschland]
-
A.
IBM
chosen
IBM is a multinational technology and consulting company known for its pioneering work in computer hardware, software, and enterprise services.
-
B.
Microsoft
Microsoft is a multinational technology company best known for its Windows operating system, Office productivity suite, and Azure cloud computing platform.
-
C.
Volkswagen Group
Volkswagen Group is a major German multinational automotive manufacturer that owns brands such as Volkswagen, Audi, Porsche, and Škoda and is one of the largest car producers in the world.
-
D.
Intel Corporation
Intel Corporation is a leading American semiconductor company best known for designing and manufacturing microprocessors that power the majority of the world’s personal computers and servers.
-
E.
BEA
BEA is a U.S. government agency that produces key economic statistics, including measures of national income, output, and growth.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24b07f4a881909e32115e84da02a3 |
completed | Feb. 28, 2026, 1:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a25ab7ec3881909356c659f4664fb8 |
completed | Feb. 28, 2026, 3:02 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.