Triple
T23005092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tronic |
E572741
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Losing Out
"Losing Out" is a track by the German electronic music producer Tronic, known for its driving techno sound and club-oriented production.
|
E1564960
|
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: Losing Out | Statement: [Tronic, hasTrack, Losing Out]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Losing Out Context triple: [Tronic, hasTrack, Losing Out]
-
A.
Losing It
"Losing It" is a popular song by Canadian country duo R. City that showcases their blend of Caribbean-influenced pop and contemporary R&B.
-
B.
Losing It All
"Losing It All" is a song by the American metalcore band Lowborn.
-
C.
Losing Things
"Losing Things" is a comedic track by George Carlin from his stand-up album "Playin' with Your Head," in which he humorously explores the frustration and absurdity of misplacing everyday items.
-
D.
Nothing to Lose
Nothing to Lose is a thriller novel by Lee Child featuring his iconic drifter hero Jack Reacher as he investigates a sinister conspiracy in two neighboring Colorado towns.
-
E.
Nothing to Lose
"Nothing to Lose" is a song featured on the punk rock album "Run for Cover."
- 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: Losing Out Triple: [Tronic, hasTrack, Losing Out]
Generated description
"Losing Out" is a track by the German electronic music producer Tronic, known for its driving techno sound and club-oriented production.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Losing Out Target entity description: "Losing Out" is a track by the German electronic music producer Tronic, known for its driving techno sound and club-oriented production.
-
A.
Losing It
"Losing It" is a popular song by Canadian country duo R. City that showcases their blend of Caribbean-influenced pop and contemporary R&B.
-
B.
Losing It All
"Losing It All" is a song by the American metalcore band Lowborn.
-
C.
Losing Things
"Losing Things" is a comedic track by George Carlin from his stand-up album "Playin' with Your Head," in which he humorously explores the frustration and absurdity of misplacing everyday items.
-
D.
Nothing to Lose
Nothing to Lose is a thriller novel by Lee Child featuring his iconic drifter hero Jack Reacher as he investigates a sinister conspiracy in two neighboring Colorado towns.
-
E.
Nothing to Lose
"Nothing to Lose" is a song featured on the punk rock album "Run for Cover."
- 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_69e245b6a3ac81908087599eefe3e365 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f18356417881908c8d6ee56bdc85f5 |
completed | April 29, 2026, 4:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bd3846500819094a1bb01797d22a5 |
completed | May 19, 2026, 3:05 a.m. |
| NEDg | Description generation | batch_6a0bd41c89708190a3df2a798ca25c99 |
completed | May 19, 2026, 3:08 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bd5263734819082ce8b1c3082243f |
completed | May 19, 2026, 3:12 a.m. |
Created at: April 17, 2026, 3:51 p.m.