Triple
T16306444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Heer |
E395926
|
entity |
| Predicate | coCreatorOf |
P806
|
FINISHED |
| Object |
Vega
Vega is an open-source visualization grammar and toolkit for creating, sharing, and exploring interactive data visualizations in a declarative JSON format.
|
E1205486
|
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: Vega | Statement: [Jeff Heer, coCreatorOf, Vega]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vega Context triple: [Jeff Heer, coCreatorOf, Vega]
-
A.
Vega
Vega is a European small-lift launch vehicle developed by the European Space Agency and partners, primarily used to place light payloads into low Earth orbit.
-
B.
Vega
Vega is a Norwegian island renowned for its UNESCO-listed archipelago, traditional eiderdown harvesting, and rich coastal birdlife.
-
C.
Vega
Vega is a common Spanish surname borne by numerous notable individuals across fields such as entertainment, sports, and politics.
-
D.
Vega
Vega is a residential locality in Haninge Municipality, Stockholm County, Sweden, known for its commuter rail station and growing suburban housing developments.
-
E.
Vega (star)
Vega is a bright, nearby A-type main-sequence star in the constellation Lyra and one of the most luminous and studied stars in the night sky.
- 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: Vega Triple: [Jeff Heer, coCreatorOf, Vega]
Generated description
Vega is an open-source visualization grammar and toolkit for creating, sharing, and exploring interactive data visualizations in a declarative JSON format.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vega Target entity description: Vega is an open-source visualization grammar and toolkit for creating, sharing, and exploring interactive data visualizations in a declarative JSON format.
-
A.
Vega
Vega is a European small-lift launch vehicle developed by the European Space Agency and partners, primarily used to place light payloads into low Earth orbit.
-
B.
Vega
Vega is a common Spanish surname borne by numerous notable individuals across fields such as entertainment, sports, and politics.
-
C.
Vega
Vega is a residential locality in Haninge Municipality, Stockholm County, Sweden, known for its commuter rail station and growing suburban housing developments.
-
D.
Vega
Vega is a Norwegian island renowned for its UNESCO-listed archipelago, traditional eiderdown harvesting, and rich coastal birdlife.
-
E.
Vega (star)
Vega is a bright, nearby A-type main-sequence star in the constellation Lyra and one of the most luminous and studied stars in the night sky.
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e288d5619081909d0f8157cc487877 |
completed | April 17, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a001fa3353c8190825b31854a97220c |
completed | May 10, 2026, 6:03 a.m. |
| NEDg | Description generation | batch_6a0020e282888190bb1d23b4876b4b75 |
completed | May 10, 2026, 6:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0021ba49808190bf69c22bc5c8d4da |
completed | May 10, 2026, 6:12 a.m. |
Created at: April 10, 2026, 5:06 a.m.