Triple
T16675440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hyaena |
E405204
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Take Me Back |
E1106335
|
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: Take Me Back | Statement: [Hyaena, hasTrack, Take Me Back]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Take Me Back Context triple: [Hyaena, hasTrack, Take Me Back]
-
A.
Take Me Back
chosen
"Take Me Back" is a song by American rock band Story of the Year, known for its energetic post-hardcore style and emotionally charged lyrics.
-
B.
Take Me Back Again
"Take Me Back Again" is a country song recorded by the American band Restless Heart.
-
C.
Take It Back
"Take It Back" is a song by the Wu-Tang Clan, released as a single from their 2007 studio album "8 Diagrams."
-
D.
Take It Back
Take It Back is a gripping legal thriller novel by British author Kia Abdullah that explores themes of prejudice, sexual assault, and the pursuit of justice through a high-stakes courtroom drama.
-
E.
Take It Back
"Take It Back" is a song featured on the collaborative R&B album "Love, Marriage & Divorce" by Toni Braxton and Babyface.
- 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_69d8838c28748190b3f5967c743940ab |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e37d6a1960819098c5e3385693a87a |
completed | April 18, 2026, 12:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a008a3ab8b481908b333b6a556a58d5 |
completed | May 10, 2026, 1:38 p.m. |
Created at: April 10, 2026, 5:19 a.m.