Triple
T14611149
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American Teen |
E342962
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Watt |
E953635
|
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: Watt | Statement: [American Teen, producer, Watt]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Watt Context triple: [American Teen, producer, Watt]
-
A.
Watt
Watt is an experimental novel by Samuel Beckett that follows the absurd, often comic journey of its title character through a bizarre and logically distorted world.
-
B.
Watt
chosen
Watt is a music producer known for working on contemporary pop and rock records, including projects like "So Far So Good."
-
C.
Watt (character)
Watt (character) is a fictional protagonist best known as the central figure in Samuel Beckett’s novel "Watt," noted for its absurdist style and exploration of logic and language.
-
D.
Joule
Joule is the SI unit of energy, named after the English physicist James Prescott Joule for his work on the mechanical equivalent of heat.
-
E.
Lammeter
Lammeter is the surname of Nancy Lammeter, a character in George Eliot’s novel "Silas Marner."
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb450e6588190a94488d8e71888c8 |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fda91f437c8190ada4d1c3708faedd |
completed | May 8, 2026, 9:13 a.m. |
Created at: April 10, 2026, 1:25 a.m.