Triple
T577402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DART for Advertisers |
E13785
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object | DoubleClick DART for Advertisers |
E13785
|
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: DoubleClick DART for Advertisers | Statement: [DART for Advertisers, alsoKnownAs, DoubleClick DART for Advertisers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DoubleClick DART for Advertisers Context triple: [DART for Advertisers, alsoKnownAs, DoubleClick DART for Advertisers]
-
A.
DART for Advertisers
chosen
DART for Advertisers is an online ad-serving and campaign management platform that enabled advertisers to create, target, deliver, and track digital advertising across websites.
-
B.
DART for Publishers
DART for Publishers was an online ad-serving and management platform used by publishers to schedule, deliver, and track digital advertising across their websites.
-
C.
DoubleClick
DoubleClick is a digital advertising technology company best known for its ad-serving and campaign management platforms that became a core part of Google’s online advertising business.
-
D.
Finding: The Self-Describing Web
"Finding: The Self-Describing Web" is a W3C Technical Architecture Group document that explains how web resources should carry or link to enough metadata and semantics to allow automated agents and humans to understand and use them without prior agreement.
-
E.
The Anatomy of a Large-Scale Hypertextual Web Search Engine
"The Anatomy of a Large-Scale Hypertextual Web Search Engine" is a seminal research paper by Sergey Brin and Larry Page that introduced the design and PageRank algorithm behind the early Google search engine.
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49b68cc808190b1ba45bdad78443d |
completed | March 1, 2026, 8:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5154fa9b48190be235b95548bbb94 |
completed | March 2, 2026, 4:42 a.m. |
Created at: March 1, 2026, 7:33 p.m.