Triple
T15263642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ethereum Virtual Machine |
E364845
|
entity |
| Predicate | inputLanguage |
P18295
|
FINISHED |
| Object |
LLL
LLL is a low-level, Lisp-like programming language used to write smart contracts that compile to Ethereum Virtual Machine bytecode.
|
E1147407
|
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: LLL | Statement: [Ethereum Virtual Machine, inputLanguage, LLL]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LLL Context triple: [Ethereum Virtual Machine, inputLanguage, LLL]
-
A.
LL
LL is the German vehicle registration code assigned to the district of Landsberg am Lech in Bavaria.
-
B.
LL
LL is a UK postcode area covering parts of North Wales, including towns such as Colwyn Bay, Llandudno, and Bangor.
-
C.
LLU
LLU is the vehicle registration code assigned to the town of Kock in Poland.
-
D.
L
L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
-
E.
L
L is the vehicle registration code used on license plates for the German city and district of Leipzig.
- 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: LLL Triple: [Ethereum Virtual Machine, inputLanguage, LLL]
Generated description
LLL is a low-level, Lisp-like programming language used to write smart contracts that compile to Ethereum Virtual Machine bytecode.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: LLL Target entity description: LLL is a low-level, Lisp-like programming language used to write smart contracts that compile to Ethereum Virtual Machine bytecode.
-
A.
LL
LL is the German vehicle registration code assigned to the district of Landsberg am Lech in Bavaria.
-
B.
LL
LL is a UK postcode area covering parts of North Wales, including towns such as Colwyn Bay, Llandudno, and Bangor.
-
C.
LLU
LLU is the vehicle registration code assigned to the town of Kock in Poland.
-
D.
L
L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
-
E.
L
L is the vehicle registration code used on license plates for the German city and district of Leipzig.
- 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_69d85a0f08408190b3c3259ae35d79d2 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0084fed0481908e452c89cba2be82 |
completed | April 15, 2026, 9:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fee5fdc21881909d87062db6fb8fb7 |
completed | May 9, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69fee714cf6c81908dc4427590eeae85 |
completed | May 9, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69feeae4731081909964bd8b1ea3dd7a |
completed | May 9, 2026, 8:05 a.m. |
Created at: April 10, 2026, 3:14 a.m.