Triple
T8426461
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marshmello |
E199006
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | Dotcom |
E330237
|
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: Dotcom | Statement: [Marshmello, alsoKnownAs, Dotcom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dotcom Context triple: [Marshmello, alsoKnownAs, Dotcom]
-
A.
Dotcom
chosen
Dotcom is a music producer known for contributing to the sound of the collaborative hip-hop project Kids See Ghosts.
-
B.
Nom.com
Nom.com was a live video streaming and social platform focused on food and cooking, co-founded by YouTube co-founder Steve Chen.
-
C.
DOT
DOT is the commonly used acronym for the United States Department of Transportation, the federal agency responsible for national transportation policy and infrastructure.
-
D.
GoDaddy
GoDaddy is a major American internet domain registrar and web hosting company known for providing online presence and website services to individuals and businesses worldwide.
-
E.
dot-com bubble
The dot-com bubble was a late-1990s to early-2000s speculative boom and crash in internet-related stocks, driven by excessive investment in unprofitable online companies.
- 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_69ca8313c99081909a5c6d83b91de5b3 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb85a37e388190b2a7ab8e6966baac |
completed | March 31, 2026, 8:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce0364f294819091ef9f39429f3fb5 |
completed | April 2, 2026, 5:49 a.m. |
Created at: March 30, 2026, 6:07 p.m.