Triple
T264710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject |
E5698
|
entity | |
| Predicate | product |
P490
|
FINISHED |
| Object | LinkedIn Ads |
E5698
|
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: LinkedIn Ads | Statement: [LinkedIn, product, LinkedIn Ads]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LinkedIn Ads Context triple: [LinkedIn, product, LinkedIn Ads]
-
A.
LinkedIn
chosen
LinkedIn is a professional networking platform and social media service focused on careers, business connections, and job opportunities.
-
B.
ADS
ADS is the stock ticker symbol under which the global sportswear company Adidas is traded on the Frankfurt Stock Exchange.
-
C.
Marketo
Marketo is a leading marketing automation software platform that helps businesses manage and optimize digital marketing campaigns and customer engagement.
-
D.
DART for Advertisers
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.
-
E.
Google Marketing Platform
Google Marketing Platform is Google's integrated suite of advertising and analytics tools that helps businesses plan, buy, measure, and optimize digital marketing campaigns across channels.
- 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_69a2587daeb081909591b9d30f80a271 |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25d8f9bbc8190a13841e4de093a66 |
completed | Feb. 28, 2026, 3:14 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a389ae45648190966804664bf4f861 |
completed | March 1, 2026, 12:34 a.m. |
Created at: Feb. 28, 2026, 2:56 a.m.