Triple
T577401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DART for Advertisers |
E13785
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
DFA
DFA is an online advertising management and ad-serving platform originally developed by DoubleClick and later integrated into Google's marketing and ad technology stack.
|
E72303
|
NE FINISHED |
How this triple was built (4 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: DFA | Statement: [DART for Advertisers, alsoKnownAs, DFA]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DFA Context triple: [DART for Advertisers, alsoKnownAs, DFA]
-
A.
FSM
FSM is the three-letter ISO 3166-1 alpha-3 country code for the Federated States of Micronesia, a Pacific island nation.
-
B.
DFG
DFG is Germany’s central self-governing research funding organization, supporting scientific and academic research across all disciplines.
-
C.
DFE
DFE is the National Rail station code for Dunfermline Town railway station in Fife, Scotland.
-
D.
DDF
DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
-
E.
Turing machine
A Turing machine is an abstract computational model that manipulates symbols on an infinite tape according to a set of rules, providing a formal foundation for the concept of algorithm and computability.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DFA Triple: [DART for Advertisers, alsoKnownAs, DFA]
Generated description
DFA is an online advertising management and ad-serving platform originally developed by DoubleClick and later integrated into Google's marketing and ad technology stack.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DFA Target entity description: DFA is an online advertising management and ad-serving platform originally developed by DoubleClick and later integrated into Google's marketing and ad technology stack.
-
A.
FSM
FSM is the three-letter ISO 3166-1 alpha-3 country code for the Federated States of Micronesia, a Pacific island nation.
-
B.
DFG
DFG is Germany’s central self-governing research funding organization, supporting scientific and academic research across all disciplines.
-
C.
DFE
DFE is the National Rail station code for Dunfermline Town railway station in Fife, Scotland.
-
D.
DDF
DDF is the commonly used abbreviation for the Dicastery for the Doctrine of the Faith, the Vatican department responsible for promoting and safeguarding Catholic doctrine.
-
E.
Turing machine
A Turing machine is an abstract computational model that manipulates symbols on an infinite tape according to a set of rules, providing a formal foundation for the concept of algorithm and computability.
- F. None of above. chosen
Provenance (5 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_69a501bfb6408190bf7e1f462f39723d |
completed | March 2, 2026, 3:19 a.m. |
| NEDg | Description generation | batch_69a5026c35408190ab22dab86c673e0f |
completed | March 2, 2026, 3:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5063ad6b481909537a97e6a81eaa4 |
completed | March 2, 2026, 3:38 a.m. |
Created at: March 1, 2026, 7:33 p.m.