Triple
T6443427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bytecode Alliance |
E138280
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Wasmer
Wasmer is a WebAssembly runtime that enables running WebAssembly modules efficiently across different platforms and programming languages.
|
E595007
|
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: Wasmer | Statement: [Bytecode Alliance, hasMember, Wasmer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wasmer Context triple: [Bytecode Alliance, hasMember, Wasmer]
-
A.
Waimes
Waimes is a municipality in the predominantly French-speaking region of Wallonia in eastern Belgium, known for its rural landscapes and proximity to the High Fens nature reserve.
-
B.
Smidovich
Smidovich is an urban-type settlement in Russia’s Jewish Autonomous Oblast, serving as a local administrative and population center in the region.
-
C.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
D.
Soral
Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
-
E.
Wakema
Wakema is a town in Myanmar’s Ayeyarwady Region, known as the birthplace of former Burmese Prime Minister U Nu.
- 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: Wasmer Triple: [Bytecode Alliance, hasMember, Wasmer]
Generated description
Wasmer is a WebAssembly runtime that enables running WebAssembly modules efficiently across different platforms and programming languages.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wasmer Target entity description: Wasmer is a WebAssembly runtime that enables running WebAssembly modules efficiently across different platforms and programming languages.
-
A.
Waimes
Waimes is a municipality in the predominantly French-speaking region of Wallonia in eastern Belgium, known for its rural landscapes and proximity to the High Fens nature reserve.
-
B.
Smidovich
Smidovich is an urban-type settlement in Russia’s Jewish Autonomous Oblast, serving as a local administrative and population center in the region.
-
C.
Martz
Martz is a surname most notably associated with Mike Martz, an American football coach known for his innovative offensive strategies in the NFL.
-
D.
Soral
Soral is a small rural municipality in southwestern Switzerland, located in the canton of Geneva near the French border.
-
E.
Wakema
Wakema is a town in Myanmar’s Ayeyarwady Region, known as the birthplace of former Burmese Prime Minister U Nu.
- 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_69c008aa61ac8190bc96715ed79fe2d8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0698b030481908b7bb4e16a8b3339 |
completed | March 22, 2026, 10:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c64bc718dc8190b186d09a17562d26 |
completed | March 27, 2026, 9:20 a.m. |
| NEDg | Description generation | batch_69c64f8c3df08190986343f78e7a066a |
completed | March 27, 2026, 9:36 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6501b1b6481908cead1450402752b |
completed | March 27, 2026, 9:38 a.m. |
Created at: March 22, 2026, 4:46 p.m.