Triple
T7764245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Pestana |
E176105
|
entity |
| Predicate | coFounded |
P104
|
FINISHED |
| Object | Omniture |
E29776
|
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: Omniture | Statement: [John Pestana, coFounded, Omniture]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Omniture Context triple: [John Pestana, coFounded, Omniture]
-
A.
Omniture
chosen
Omniture was a leading web analytics and online marketing optimization company best known for its SiteCatalyst platform before being acquired by Adobe.
-
B.
Coremetrics
Coremetrics is a web analytics and digital marketing optimization company known for providing businesses with detailed insights into online customer behavior and campaign performance.
-
C.
Webtrends
Webtrends is a digital analytics company known for providing web traffic measurement and marketing optimization solutions for websites and online campaigns.
-
D.
Adobe Audience Manager
Adobe Audience Manager is a data management platform that helps businesses collect, organize, and activate audience data for targeted advertising and personalized marketing across channels.
-
E.
IAB Tech Lab
IAB Tech Lab is a global industry body that develops technical standards and solutions to support and improve digital advertising.
- 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_69c69962923c8190ac74d28b4f9fe0a0 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c704076ba08190bcde971f7e4448c6 |
completed | March 27, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8c7de604c81908f503e1553795d38 |
completed | March 29, 2026, 6:34 a.m. |
Created at: March 27, 2026, 4:09 p.m.