Triple
T20436465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Takin' It Back |
E501261
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Drama Queen |
—
|
NE NERFINISHED |
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: Drama Queen | Statement: [Takin' It Back, hasPart, Drama Queen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Drama Queen Context triple: [Takin' It Back, hasPart, Drama Queen]
-
A.
Drama Queen
Drama Queen is a reggaeton album by Puerto Rican artist Ivy Queen that showcases her powerful vocals and assertive, feminist lyrical style.
-
B.
Drama Queen
chosen
"Drama Queen" is a song by American punk rock band Green Day from their album ¡Tré!.
-
C.
Queen of Queens
Queen of Queens is the exalted royal title borne by Tamar of Georgia, reflecting her status as a supreme and sovereign monarch in medieval Georgian history.
-
D.
King of Queens
King of Queens is the 2014 debut studio album by Nigerian singer Yemi Alade, blending Afro-pop and dance music that helped establish her as a leading figure in contemporary African music.
-
E.
King of Queens
King of Queens is an American sitcom that follows the everyday misadventures of a delivery driver, his wife, and her eccentric father living together in Queens, New York.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4ab3cfc8190ac9bf32e932316b1 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e685ef5fc8819089e3f97a63a52f86 |
completed | April 20, 2026, 8 p.m. |
Created at: April 16, 2026, 11:31 a.m.