Triple
T16753043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Take a Bow |
E407131
|
entity |
| Predicate | performedOnTour |
P7952
|
FINISHED |
| Object | Good Girl Gone Bad Tour |
E87100
|
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: Good Girl Gone Bad Tour | Statement: [Take a Bow, performedOnTour, Good Girl Gone Bad Tour]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Good Girl Gone Bad Tour Context triple: [Take a Bow, performedOnTour, Good Girl Gone Bad Tour]
-
A.
Good Girl Gone Bad
Good Girl Gone Bad is a popular reggae song by Jamaican singer Tarrus Riley, known for its smooth vocals and romantic, roots-influenced style.
-
B.
Good Girl Gone Bad
chosen
Good Girl Gone Bad is Rihanna's critically acclaimed 2007 pop and R&B album that marked her transition to a more edgy, mature image and sound.
-
C.
Hold the Girl Tour
The Hold the Girl Tour is a concert tour by Japanese-British pop artist Rina Sawayama in support of her second studio album, "Hold the Girl."
-
D.
Bad Girl
"Bad Girl" is a high-energy R&B/pop single by Danity Kane known for its club-ready production and confident, empowering lyrics.
-
E.
Bad Girl
"Bad Girl" is a track from the album "Erotica," known for its provocative themes and sensual style.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa28fd3c8190972e2e69ea7dece0 |
completed | April 18, 2026, 3:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00a52402848190b029cb0be31b4c74 |
completed | May 10, 2026, 3:32 p.m. |
Created at: April 10, 2026, 5:21 a.m.