Triple
T33445797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MKTO |
E856494
|
entity |
| Predicate | hasNotableSongCharacteristic |
P9125
|
FINISHED |
| Object | catchy pop hooks |
—
|
LITERAL 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: catchy pop hooks | Statement: [MKTO, hasNotableSongCharacteristic, catchy pop hooks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableSongCharacteristic Context triple: [MKTO, hasNotableSongCharacteristic, catchy pop hooks]
-
A.
notableSongCharacteristic
chosen
Indicates that a song is distinguished by a particular notable feature or quality, such as style, structure, or performance trait.
-
B.
hasNotableSongType
Indicates that an entity is associated with a specific type or category of notable song.
-
C.
hasSpecialSong
Indicates that one entity possesses or is associated with a particular song that is unique, distinctive, or specially designated for it.
-
D.
hasNotableSongNumber
Indicates that an entity is associated with a specific song identified by its notable number or index within a collection or sequence.
-
E.
hasNotableBeat
Indicates that an entity (such as a journalist or reporter) is professionally assigned to cover a specific topic, area, or subject as their primary reporting focus.
- F. None of above.
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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a01beacf8a88190ac643a75c7a0efc4 |
completed | May 11, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_6a01be152c8c8190bb19d64a683e2aae |
completed | May 11, 2026, 11:31 a.m. |
Created at: May 1, 2026, 1:37 a.m.