Triple
T22126133
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glassheart |
E546794
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Ammar Malik |
—
|
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: Ammar Malik | Statement: [Glassheart, producer, Ammar Malik]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ammar Malik Context triple: [Glassheart, producer, Ammar Malik]
-
A.
Ammar Malik
chosen
Ammar Malik is an American songwriter known for co-writing major pop hits for artists like Maroon 5 and Gym Class Heroes.
-
B.
Ameer Ismail
Ameer Ismail is an American football coach and former linebacker known for his standout college career at Western Michigan and subsequent coaching roles in indoor and arena football.
-
C.
Aarif Sheikh
Aarif Sheikh is an Indian film editor known for his work on acclaimed Hindi movies, including the comedy-drama "Hindi Medium."
-
D.
Armaan Ali
Armaan Ali is a fictional character from the Indian film "Well Done Abba."
-
E.
Walid Nadeem
Walid Nadeem is a fictional character known primarily as the romantic partner of Frank Bledsoe in the film "Uncle Frank."
- 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_69e11e39bf348190b541bfa16a7b71e0 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12981ac008190aafb516f2a28fefc |
completed | April 28, 2026, 9:41 p.m. |
Created at: April 16, 2026, 8:31 p.m.