Triple
T13494793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ski Mask the Slump God |
E320728
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | La La |
E425038
|
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: La La | Statement: [Ski Mask the Slump God, notableWork, La La]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: La La Context triple: [Ski Mask the Slump God, notableWork, La La]
-
A.
La La
chosen
"La La" is a pop-rock song by American singer Ashlee Simpson from her debut album "Autobiography," known for its edgy lyrics and rebellious tone.
-
B.
Lala
Lala is a small town in the Hailakandi district of the Indian state of Assam.
-
C.
Lala
Lala is an Indian honorific title traditionally used as a respectful prefix for educated or distinguished men, particularly in North India.
-
D.
La La La
"La La La" is a 2013 hit single by British producer Naughty Boy featuring singer Sam Smith, known for its catchy hook and emotionally charged electronic pop sound.
-
E.
LOLA
LOLA is the commonly used abbreviation for "Law & Order: LA," a short-lived spin-off of the long-running "Law & Order" television franchise set in Los Angeles.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf4da2c88190a867b53529d39545 |
completed | April 12, 2026, 2:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7463d3a948190aab07a25fd903d4e |
completed | May 3, 2026, 12:57 p.m. |
Created at: April 9, 2026, 9:43 p.m.