Triple
T1775021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Linux/m68k |
E38957
|
entity |
| Predicate | supportsPlatform |
P203
|
FINISHED |
| Object |
BVME6000
BVME6000 is a Motorola 680x0-based VMEbus single-board computer commonly used in embedded and industrial systems.
|
E198695
|
NE FINISHED |
How this triple was built (4 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: BVME6000 | Statement: [Linux/m68k, supportsPlatform, BVME6000]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: BVME6000 Context triple: [Linux/m68k, supportsPlatform, BVME6000]
-
A.
BB-63
BB-63 is the hull number of USS Missouri, a famous Iowa-class battleship best known as the site of Japan’s formal surrender in World War II.
-
B.
BdM
BdM is the central bank of Mexico, responsible for maintaining the country’s monetary stability and issuing its currency.
-
C.
VBB
VBB is the public transport authority and fare network that coordinates and integrates regional and urban transit services across Berlin and the surrounding Brandenburg region.
-
D.
BOE
BOE is the standard abbreviation for Biomedical Optics Express, a peer-reviewed scientific journal focusing on research in biomedical optics and photonics.
-
E.
B6
B6 is the IATA airline designator used to identify JetBlue Airways on tickets, schedules, and flight information systems.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: BVME6000 Triple: [Linux/m68k, supportsPlatform, BVME6000]
Generated description
BVME6000 is a Motorola 680x0-based VMEbus single-board computer commonly used in embedded and industrial systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: BVME6000 Target entity description: BVME6000 is a Motorola 680x0-based VMEbus single-board computer commonly used in embedded and industrial systems.
-
A.
BB-63
BB-63 is the hull number of USS Missouri, a famous Iowa-class battleship best known as the site of Japan’s formal surrender in World War II.
-
B.
BdM
BdM is the central bank of Mexico, responsible for maintaining the country’s monetary stability and issuing its currency.
-
C.
VBB
VBB is the public transport authority and fare network that coordinates and integrates regional and urban transit services across Berlin and the surrounding Brandenburg region.
-
D.
BOE
BOE is the standard abbreviation for Biomedical Optics Express, a peer-reviewed scientific journal focusing on research in biomedical optics and photonics.
-
E.
B6
B6 is the IATA airline designator used to identify JetBlue Airways on tickets, schedules, and flight information systems.
- F. None of above. chosen
Provenance (5 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa64b6c4a88190ab2f75c8d4814f11 |
completed | March 6, 2026, 5:23 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9982d208190b0c29ee1141e91b0 |
completed | March 8, 2026, 4:53 p.m. |
| NEDg | Description generation | batch_69adab03a5448190b42966adcd8afbde |
completed | March 8, 2026, 4:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adaeabff6c8190b19bc6478a28641c |
completed | March 8, 2026, 5:15 p.m. |
Created at: March 4, 2026, 7:31 p.m.