Triple
T23262600
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Never Liked You |
E582052
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Mally Mall |
E828386
|
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: Mally Mall | Statement: [I Never Liked You, producer, Mally Mall]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mally Mall Context triple: [I Never Liked You, producer, Mally Mall]
-
A.
Mally Mall
chosen
Mally Mall is an American hip-hop producer and entrepreneur known for his work with prominent rap and R&B artists and appearances on reality television.
-
B.
Mallrat
Mallrat is an Australian indie-pop singer and songwriter known for her dreamy, introspective tracks and rising international profile.
-
C.
Down in the Mall
"Down in the Mall" is a track from Warren Zevon’s concept album "Transverse City," contributing to its dystopian, technology-saturated narrative.
-
D.
The Mart
The Mart is a massive commercial building in Chicago, historically known as the Merchandise Mart, that serves as a major hub for wholesale showrooms, offices, and design centers.
-
E.
The Malls
The Malls is a central shopping complex in Basingstoke, England, featuring a range of retail stores and services.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194caaf208190931923744692180d |
completed | April 29, 2026, 5:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c3f7050388190a0848037c96049c0 |
completed | May 19, 2026, 10:46 a.m. |
Created at: April 17, 2026, 4:11 p.m.