Triple
T17653984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corona Borealis |
E429569
|
entity |
| Predicate | brightestStar |
P6956
|
FINISHED |
| Object |
Alphecca
Alphecca is a bright binary star system in the constellation Corona Borealis, notable as one of the sky’s prominent eclipsing variables.
|
E1280290
|
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: Alphecca | Statement: [Corona Borealis, brightestStar, Alphecca]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alphecca Context triple: [Corona Borealis, brightestStar, Alphecca]
-
A.
Abellinum
Abellinum was an ancient town of the Samnite and later Roman world in southern Italy, located in the region historically known as Samnium.
-
B.
Ascella
Ascella is a prominent multiple star system in the constellation Sagittarius, known for being one of its brightest and most easily visible stars.
-
C.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
D.
Avelia
Avelia is a family of high-speed trainsets developed by Alstom and used in various advanced rail networks around the world.
-
E.
Atheras
Atheras is a mountainous region on the Greek island of Ikaria, known for its rugged terrain and scenic landscapes.
- 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: Alphecca Triple: [Corona Borealis, brightestStar, Alphecca]
Generated description
Alphecca is a bright binary star system in the constellation Corona Borealis, notable as one of the sky’s prominent eclipsing variables.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Alphecca Target entity description: Alphecca is a bright binary star system in the constellation Corona Borealis, notable as one of the sky’s prominent eclipsing variables.
-
A.
Abellinum
Abellinum was an ancient town of the Samnite and later Roman world in southern Italy, located in the region historically known as Samnium.
-
B.
Ascella
Ascella is a prominent multiple star system in the constellation Sagittarius, known for being one of its brightest and most easily visible stars.
-
C.
Faventia
Faventia is the ancient Roman name for the Italian city of Faenza, historically known as an important settlement in northern Italy.
-
D.
Avelia
Avelia is a family of high-speed trainsets developed by Alstom and used in various advanced rail networks around the world.
-
E.
Atheras
Atheras is a mountainous region on the Greek island of Ikaria, known for its rugged terrain and scenic landscapes.
- 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_69d889e2c2608190b762e76d9b2262f1 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e46e3ed8b08190a00efdad9740bf6f |
completed | April 19, 2026, 5:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a021656351081908bc8f4e7eabbf8f8 |
completed | May 11, 2026, 5:48 p.m. |
| NEDg | Description generation | batch_6a021747bc488190bf008b895d7f085b |
completed | May 11, 2026, 5:52 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0217e07bd08190a727c42742a467c3 |
completed | May 11, 2026, 5:54 p.m. |
Created at: April 10, 2026, 6:05 a.m.