Triple
T20885029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abella |
E514254
|
entity |
| Predicate | developedBy |
P73
|
FINISHED |
| Object |
Alwen Tiu
Alwen Tiu is a computer scientist known for his work in formal methods and logic, including the development of the Abella interactive theorem prover.
|
E1455293
|
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: Alwen Tiu | Statement: [Abella, developedBy, Alwen Tiu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alwen Tiu Context triple: [Abella, developedBy, Alwen Tiu]
-
A.
Glynis
Glynis is a feminine given name most notably associated with the British actress and singer Glynis Johns.
-
B.
Dryna
Dryna is an island located within the municipality of Haram in Møre og Romsdal county, Norway.
-
C.
Gwynplaine
Gwynplaine is the disfigured, perpetually grinning protagonist of Victor Hugo’s novel "The Man Who Laughs," whose tragic appearance inspired later characters like the Joker.
-
D.
Welun
Welun is the German name for the Polish town of Wieluń, known for being one of the first places bombed at the start of World War II.
-
E.
Ethelyn
Ethelyn is a feminine given name, considered a variant of Ethel, that saw occasional use in English-speaking countries in the late 19th and early 20th centuries.
- 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: Alwen Tiu Triple: [Abella, developedBy, Alwen Tiu]
Generated description
Alwen Tiu is a computer scientist known for his work in formal methods and logic, including the development of the Abella interactive theorem prover.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alwen Tiu Target entity description: Alwen Tiu is a computer scientist known for his work in formal methods and logic, including the development of the Abella interactive theorem prover.
-
A.
Glynis
Glynis is a feminine given name most notably associated with the British actress and singer Glynis Johns.
-
B.
Dryna
Dryna is an island located within the municipality of Haram in Møre og Romsdal county, Norway.
-
C.
Gwynplaine
Gwynplaine is the disfigured, perpetually grinning protagonist of Victor Hugo’s novel "The Man Who Laughs," whose tragic appearance inspired later characters like the Joker.
-
D.
Welun
Welun is the German name for the Polish town of Wieluń, known for being one of the first places bombed at the start of World War II.
-
E.
Ethelyn
Ethelyn is a feminine given name, considered a variant of Ethel, that saw occasional use in English-speaking countries in the late 19th and early 20th centuries.
- 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_69e0b4f733f081908a401c0b7beb0b9f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c67c9d1c81908031eb77c124f119 |
completed | April 21, 2026, 12:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0913a67fec819093ea6b8388f983f0 |
completed | May 17, 2026, 1:02 a.m. |
| NEDg | Description generation | batch_6a0914d5ffb081909f7eca2593de8a10 |
completed | May 17, 2026, 1:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0915665ec081909695a6c4aba50dbc |
completed | May 17, 2026, 1:09 a.m. |
Created at: April 16, 2026, 12:46 p.m.