Triple
T15045505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naughty Boy |
E379214
|
entity |
| Predicate | associatedAct |
P37
|
FINISHED |
| Object | Lily Allen |
E87106
|
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: Lily Allen | Statement: [Naughty Boy, associatedAct, Lily Allen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lily Allen Context triple: [Naughty Boy, associatedAct, Lily Allen]
-
A.
Lily Allen
chosen
Lily Allen is an English singer, songwriter, and author known for her sharp, witty lyrics and pop hits such as "Smile" and "The Fear."
-
B.
Pixie Lott
Pixie Lott is an English singer, songwriter, and actress who rose to fame with her 2009 debut single "Mama Do (Uh Oh, Uh Oh)" and subsequent pop hits.
-
C.
Ellie Goulding
Ellie Goulding is an English singer-songwriter known for her ethereal vocals and synth-pop hits such as "Lights" and "Love Me Like You Do."
-
D.
Lydia Spelman
Lydia Spelman was a member of the prominent Spelman family of Ohio, related to philanthropist Laura Spelman Rockefeller.
-
E.
Sophie Ellis-Bextor
Sophie Ellis-Bextor is an English singer and songwriter best known for her fusion of pop, disco, and electronic music, including hits like "Murder on the Dancefloor."
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded830c3c08190a87b81abbbb75377 |
completed | April 15, 2026, 12:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe9de54380819084568664b63322d2 |
completed | May 9, 2026, 2:37 a.m. |
Created at: April 10, 2026, 3 a.m.