Triple
T8090933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicole Shanahan |
E188857
|
entity |
| Predicate | founded |
P104
|
FINISHED |
| Object | ClearAccessIP |
E711410
|
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: ClearAccessIP | Statement: [Nicole Shanahan, founded, ClearAccessIP]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ClearAccessIP Context triple: [Nicole Shanahan, founded, ClearAccessIP]
-
A.
ClearAccessIP
chosen
ClearAccessIP is a technology company that provides AI-driven intellectual property management and patent analytics solutions for businesses and legal professionals.
-
B.
I-PASS
I-PASS is an electronic toll collection system used on Illinois tollways that allows drivers to pay tolls automatically without stopping.
-
C.
SL Access
SL Access is Stockholm's public transport smart card and ticketing system used for travel on buses, trains, and other SL services.
-
D.
Access
Access is Microsoft's desktop database management system that enables users to create, manage, and analyze relational databases through a graphical interface and integrated tools.
-
E.
IP
IP is the acronym for Infraestruturas de Portugal, the Portuguese state-owned company responsible for managing the country’s road and rail infrastructure.
- 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_69ca82b7b3e88190b9041ab0ef28b3cb |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb421fb8348190b6495394d498d3f4 |
completed | March 31, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc93ff6a108190ac60218ec2716c60 |
completed | April 1, 2026, 3:41 a.m. |
Created at: March 30, 2026, 5:29 p.m.