Triple
T18172947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Napster |
E435076
|
entity |
| Predicate | influenced |
P9
|
FINISHED |
| Object | Gnutella |
—
|
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: Gnutella | Statement: [Napster, influenced, Gnutella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gnutella Context triple: [Napster, influenced, Gnutella]
-
A.
Gnutella
chosen
Gnutella is a decentralized peer-to-peer file-sharing protocol and network that enabled users to share files directly without relying on a central server.
-
B.
Kazaa
Kazaa is a peer-to-peer file-sharing application that became widely known in the early 2000s for enabling users to share music, videos, and other digital media over the internet.
-
C.
BitTorrent
BitTorrent is a peer-to-peer file sharing protocol that enables efficient distribution of large amounts of data across many users without relying on a central server.
-
D.
Napster
Napster is a pioneering peer-to-peer file sharing service that revolutionized digital music distribution in the late 1990s and early 2000s.
-
E.
eDonkey2000
eDonkey2000 was a popular peer-to-peer file-sharing application and network from the early 2000s, known for decentralized distribution of large files such as movies, music, and software.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4df56d0a88190af3f407d2a3bb74f |
completed | April 19, 2026, 1:57 p.m. |
Created at: April 10, 2026, 10:30 a.m.