Triple
T9904768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noel "Detail" Fisher |
E184976
|
entity |
| Predicate | hasAlias |
P455
|
FINISHED |
| Object | Detail |
E245935
|
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: Detail | Statement: [Noel "Detail" Fisher, hasAlias, Detail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Detail Context triple: [Noel "Detail" Fisher, hasAlias, Detail]
-
A.
Detail
chosen
Detail is an American record producer and songwriter known for crafting hit R&B and hip-hop tracks for major artists such as Beyoncé and Lil Wayne.
-
B.
Devil in the Details
"Devil in the Details" is a song by the indie rock band Bright Eyes from their electronically influenced album *Digital Ash in a Digital Urn*.
-
C.
Extra
Extra is a popular sugar-free chewing gum brand produced by the Wrigley Company, known for its long-lasting flavor and wide variety of mint and fruit options.
-
D.
Extra
Extra is an American entertainment news television program that covers celebrity news, gossip, and pop culture.
-
E.
Dete
Dete is a small town in western Zimbabwe, known as a gateway settlement near Hwange National Park and the town of Hwange.
- 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_69ca8296165881908ca4750701af1f29 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cdb4e641e881909dfba78fcb96c433 |
completed | April 2, 2026, 12:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1eb2c1d5c8190b6f1c43254487893 |
completed | April 5, 2026, 4:55 a.m. |
Created at: March 30, 2026, 8:40 p.m.