Triple
T12568393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Florian Seiche |
E295531
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | HMD Global |
E59624
|
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: HMD Global | Statement: [Florian Seiche, employer, HMD Global]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HMD Global Context triple: [Florian Seiche, employer, HMD Global]
-
A.
HMD Global
chosen
HMD Global is a Finnish consumer electronics company best known for designing and marketing Nokia-branded mobile phones and smartphones.
-
B.
HMD
HMD is the commonly used abbreviation for Holocaust Memorial Day in the United Kingdom, a national day of remembrance for the victims of the Holocaust and subsequent genocides.
-
C.
HMD
HMD is the three-letter station code used to identify Hampstead tube station on the London Underground network.
-
D.
Nokia
Nokia is a Finnish multinational telecommunications and consumer electronics company best known for its historic leadership in mobile phones and its current focus on network infrastructure and 5G technologies.
-
E.
Huawei
Huawei is a major Chinese multinational technology company best known globally for its telecommunications equipment, smartphones, and role in 5G network infrastructure.
- 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_69d6ad9cac2c81908e8a7bed82d1e21d |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954a325948190994bcfc9d571a3a8 |
completed | April 10, 2026, 7:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f67c6c21348190b851fce31df307e2 |
completed | May 2, 2026, 10:36 p.m. |
Created at: April 8, 2026, 11:50 p.m.