Triple
T13938655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Pleasure Principle |
E335182
|
entity |
| Predicate | followedBy |
P78
|
FINISHED |
| Object |
Telekon
Telekon is a 1980 synth-pop album by Gary Numan that continued his pioneering electronic sound with darker, more atmospheric themes.
|
E1070930
|
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: Telekon | Statement: [The Pleasure Principle, followedBy, Telekon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Telekon Context triple: [The Pleasure Principle, followedBy, Telekon]
-
A.
Teklicon
Teklicon is a technology consulting and expert witness firm known for employing semiconductor pioneer Marcian "Ted" Hoff.
-
B.
Telecip
Telecip is a French film production company best known for backing the 1976 Academy Award–winning war satire "Black and White in Color."
-
C.
Telegin
Telegin is a minor but memorable character in Anton Chekhov’s play "Uncle Vanya," known for his shabby gentility, loyalty, and melancholy humor.
-
D.
Tronic
Tronic is a critically acclaimed studio album by Detroit rapper and producer Black Milk, known for its futuristic production and intricate lyricism.
-
E.
Teles
Teles is a relatively obscure figure in Greek mythology, known primarily as one of the many children in the royal lineage associated with the hero Perseus.
- 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: Telekon Triple: [The Pleasure Principle, followedBy, Telekon]
Generated description
Telekon is a 1980 synth-pop album by Gary Numan that continued his pioneering electronic sound with darker, more atmospheric themes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Telekon Target entity description: Telekon is a 1980 synth-pop album by Gary Numan that continued his pioneering electronic sound with darker, more atmospheric themes.
-
A.
Teklicon
Teklicon is a technology consulting and expert witness firm known for employing semiconductor pioneer Marcian "Ted" Hoff.
-
B.
Telecip
Telecip is a French film production company best known for backing the 1976 Academy Award–winning war satire "Black and White in Color."
-
C.
Telegin
Telegin is a minor but memorable character in Anton Chekhov’s play "Uncle Vanya," known for his shabby gentility, loyalty, and melancholy humor.
-
D.
Tronic
Tronic is a critically acclaimed studio album by Detroit rapper and producer Black Milk, known for its futuristic production and intricate lyricism.
-
E.
Teles
Teles is a relatively obscure figure in Greek mythology, known primarily as one of the many children in the royal lineage associated with the hero Perseus.
- 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_69d81c6081b88190b53e317c3370c8fe |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf5cc8c8190bea74291702b2925 |
completed | April 14, 2026, 12:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce89d2348190b5a50376c2b8248c |
completed | May 3, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69f7cfe8dca08190825b8e1bbfe411a6 |
completed | May 3, 2026, 10:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69fb5504702081908a1492f1a8e24434 |
completed | May 6, 2026, 2:49 p.m. |
Created at: April 9, 2026, 10:17 p.m.