Triple
T12321492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Good Time |
E293737
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Tekno |
E298317
|
NE FINISHED |
How this triple was built (2 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: Tekno | Statement: [A Good Time, producer, Tekno]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tekno Context triple: [A Good Time, producer, Tekno]
-
A.
Tekno
chosen
Tekno is a Nigerian singer, songwriter, and record producer known for his Afrobeat and Afropop hit songs and dance-oriented sound.
-
B.
Tech
The Tech is a river in southern France that flows through the Pyrénées-Orientales in the Occitanie region before emptying into the Mediterranean Sea.
-
C.
Tech
Tech is a highly intelligent and tech-savvy clone commando in Star Wars: The Bad Batch, known for his analytical mind, technical expertise, and role as the squad’s systems and communications specialist.
-
D.
Technologic
"Technologic" is a 2005 electronic dance track by French duo Daft Punk, known for its robotic vocals listing technology-related commands over a minimalist, catchy beat.
-
E.
Tek-Tools
Tek-Tools was a software company known for its storage and virtualization management solutions before being acquired by SolarWinds.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f4c2b548190938fff9427f07dc7 |
completed | April 10, 2026, 6:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f61e8aa94881908e4c184062037ab5 |
completed | May 2, 2026, 3:55 p.m. |
Created at: April 8, 2026, 9:53 p.m.