Triple
T12481506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tekno |
E298317
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Wash
"Wash" is a popular electronic dance music track by Nigerian producer and DJ Tekno, known for its catchy melody and club-friendly beat.
|
E985614
|
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: Wash | Statement: [Tekno, notableWork, Wash]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wash Context triple: [Tekno, notableWork, Wash]
-
A.
Wash.
Wash. is the standard legal citation abbreviation used to refer to decisions of the Washington Supreme Court.
-
B.
Entwash
Entwash is a major river in J.R.R. Tolkien’s Middle-earth that flows from Fangorn Forest through Rohan before joining the Great River Anduin.
-
C.
Tide
Tide is a leading American laundry detergent brand known for its powerful stain-removal formulas and wide range of fabric care products.
-
D.
Shampoo
"Shampoo" is a 1975 satirical romantic comedy film set on the eve of the 1968 U.S. presidential election, starring Warren Beatty as a Beverly Hills hairdresser entangled in complex romantic and social relationships.
-
E.
Bernasconi Wash
Bernasconi Wash is a desert stream channel in Riverside County, California, that feeds into the area impounded by Perris Dam in Lake Perris State Recreation Area.
- 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: Wash Triple: [Tekno, notableWork, Wash]
Generated description
"Wash" is a popular electronic dance music track by Nigerian producer and DJ Tekno, known for its catchy melody and club-friendly beat.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wash Target entity description: "Wash" is a popular electronic dance music track by Nigerian producer and DJ Tekno, known for its catchy melody and club-friendly beat.
-
A.
Wash.
Wash. is the standard legal citation abbreviation used to refer to decisions of the Washington Supreme Court.
-
B.
Entwash
Entwash is a major river in J.R.R. Tolkien’s Middle-earth that flows from Fangorn Forest through Rohan before joining the Great River Anduin.
-
C.
Tide
Tide is a leading American laundry detergent brand known for its powerful stain-removal formulas and wide range of fabric care products.
-
D.
Shampoo
"Shampoo" is a 1975 satirical romantic comedy film set on the eve of the 1968 U.S. presidential election, starring Warren Beatty as a Beverly Hills hairdresser entangled in complex romantic and social relationships.
-
E.
Bernasconi Wash
Bernasconi Wash is a desert stream channel in Riverside County, California, that feeds into the area impounded by Perris Dam in Lake Perris State Recreation Area.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dcef6548190a6d29375bdabd17d |
completed | April 10, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f29307c8190b024d889d45ba9f7 |
completed | May 2, 2026, 6:15 p.m. |
| NEDg | Description generation | batch_69f6437e88c881909b7f1d55c11b0825 |
completed | May 2, 2026, 6:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f644464c0c8190a8d4ea4914d32e7f |
completed | May 2, 2026, 6:36 p.m. |
Created at: April 8, 2026, 9:56 p.m.