Triple
T16117791
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expo permanent markers |
E391048
|
entity |
| Predicate | brandFamily |
P11218
|
FINISHED |
| Object | Expo markers |
E88623
|
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: Expo markers | Statement: [Expo permanent markers, brandFamily, Expo markers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Expo markers Context triple: [Expo permanent markers, brandFamily, Expo markers]
-
A.
Expo
Expo is an open-source platform and toolchain for building, deploying, and iterating on React Native applications.
-
B.
Expo
chosen
Expo is a popular brand best known for its dry-erase markers and related whiteboard accessories commonly used in schools, offices, and homes.
-
C.
The Expo
The Expo is a well-known multipurpose event and exhibition venue in Portland, Oregon, hosting trade shows, conventions, and community events.
-
D.
Expo magazine
Expo magazine is a Swedish anti-racist and anti-fascist publication known for investigating and exposing far-right extremism and xenophobia.
-
E.
Expo Go
Expo Go is a mobile app that lets developers instantly run and preview React Native projects on their devices without building native binaries.
- 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_69d87f1a8dd881909f1de6ef78849874 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2016c10a081909b2d23ecea153a9c |
completed | April 17, 2026, 9:46 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2a44cb48190abe3b1ea27349734 |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5 a.m.