Triple
T17260451
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terraform |
E418993
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Bluegreen
Bluegreen is a track by the electronic music producer Terraform, known for its atmospheric soundscapes and immersive production.
|
E1259348
|
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: Bluegreen | Statement: [Terraform, hasTrack, Bluegreen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bluegreen Context triple: [Terraform, hasTrack, Bluegreen]
-
A.
Brightview
Brightview is a small rural locality situated within Queensland’s Somerset Region in Australia.
-
B.
Mellon Green
Mellon Green is a small urban park and public green space in downtown Pittsburgh, Pennsylvania, known for its lawn, fountain, and use as a gathering spot amid surrounding office towers.
-
C.
Balgreen
Balgreen is a residential suburb in the west of Edinburgh, Scotland, known for its local parkland and proximity to the city’s tram and rail links.
-
D.
Evergreen Group
Evergreen Group is a Taiwan-based global conglomerate best known for its shipping, aviation, and logistics businesses.
-
E.
Hollenburg
Hollenburg is a village and wine-growing district of Krems an der Donau in Lower Austria, known for its historic castle and location along the Danube.
- 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: Bluegreen Triple: [Terraform, hasTrack, Bluegreen]
Generated description
Bluegreen is a track by the electronic music producer Terraform, known for its atmospheric soundscapes and immersive production.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bluegreen Target entity description: Bluegreen is a track by the electronic music producer Terraform, known for its atmospheric soundscapes and immersive production.
-
A.
Brightview
Brightview is a small rural locality situated within Queensland’s Somerset Region in Australia.
-
B.
Mellon Green
Mellon Green is a small urban park and public green space in downtown Pittsburgh, Pennsylvania, known for its lawn, fountain, and use as a gathering spot amid surrounding office towers.
-
C.
Balgreen
Balgreen is a residential suburb in the west of Edinburgh, Scotland, known for its local parkland and proximity to the city’s tram and rail links.
-
D.
Evergreen Group
Evergreen Group is a Taiwan-based global conglomerate best known for its shipping, aviation, and logistics businesses.
-
E.
Hollenburg
Hollenburg is a village and wine-growing district of Krems an der Donau in Lower Austria, known for its historic castle and location along the Danube.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6fa940819089046d1b12dede2c |
completed | April 19, 2026, 1:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a017101d5dc8190ac6507344897b0f3 |
completed | May 11, 2026, 6:02 a.m. |
| NEDg | Description generation | batch_6a0174d0014881908b99546055f9a781 |
completed | May 11, 2026, 6:18 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01758edf5c8190be0cfb3f7ba88796 |
completed | May 11, 2026, 6:22 a.m. |
Created at: April 10, 2026, 5:39 a.m.