Triple
T10848156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MNEK |
E256069
|
entity |
| Predicate | hasCollaboratedWith |
P8554
|
FINISHED |
| Object |
KDA
KDA is a British electronic music production project best known for its club-ready house tracks and high-profile collaborations with pop and dance artists.
|
E889738
|
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: KDA | Statement: [MNEK, hasCollaboratedWith, KDA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: KDA Context triple: [MNEK, hasCollaboratedWith, KDA]
-
A.
Ka
Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
-
B.
Ka
Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
-
C.
DK
DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
-
D.
DK
DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
-
E.
DK
DK is the standard scholarly abbreviation for the Diels–Kranz collection of pre-Socratic Greek philosophical fragments.
- 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: KDA Triple: [MNEK, hasCollaboratedWith, KDA]
Generated description
KDA is a British electronic music production project best known for its club-ready house tracks and high-profile collaborations with pop and dance artists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: KDA Target entity description: KDA is a British electronic music production project best known for its club-ready house tracks and high-profile collaborations with pop and dance artists.
-
A.
Ka
Ka is the introspective poet and protagonist of Orhan Pamuk’s novel "Snow," whose return to Turkey and entanglement in political and personal conflicts drive the story’s exploration of faith, identity, and modernity.
-
B.
Ka
Ka was an early ancient Egyptian king of the First Dynasty period, known from tomb inscriptions at Abydos and considered one of the first rulers to use a royal serekh.
-
C.
DK
DK is a British illustrated reference publisher best known for its highly visual nonfiction books for children and adults across topics like science, history, travel, and nature.
-
D.
DK
DK is the ISO 3166-1 alpha-2 country code for Denmark, a Nordic nation in Northern Europe.
-
E.
DK
DK is an abbreviation for Danity Kane, an American girl group formed on the MTV reality show "Making the Band."
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75114ca988190a0e730131adb2df0 |
completed | April 9, 2026, 7:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb170e714819097babb2b850342d2 |
completed | April 14, 2026, 9:28 p.m. |
| NEDg | Description generation | batch_69dec255abb08190bf93573c41aa35e9 |
completed | April 14, 2026, 10:40 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69dec7c48c3c81909365b901830f0906 |
completed | April 14, 2026, 11:03 p.m. |
Created at: April 8, 2026, 9:20 p.m.