Triple
T22649550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expo toolchain |
E559056
|
entity |
| Predicate | maintainedBy |
P86
|
FINISHED |
| Object | Expo (company) |
—
|
NE NERFINISHED |
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 (company) | Statement: [Expo toolchain, maintainedBy, Expo (company)]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Expo (company) Context triple: [Expo toolchain, maintainedBy, Expo (company)]
-
A.
Expo, Inc.
chosen
Expo, Inc. is the company behind the Expo platform and tools that streamline building, deploying, and managing React Native applications.
-
B.
Expo
Expo is an open-source platform and toolchain for building, deploying, and iterating on React Native applications.
-
C.
Expo
Expo is a popular brand best known for its dry-erase markers and related whiteboard accessories commonly used in schools, offices, and homes.
-
D.
The Expo
The Expo is a well-known multipurpose event and exhibition venue in Portland, Oregon, hosting trade shows, conventions, and community events.
-
E.
Expo/Western
Expo/Western is a Los Angeles Metro Rail station on the E Line located at the intersection of Exposition Boulevard and Western Avenue in Los Angeles, California.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245489dd88190b1f674acf61c8769 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1703a84b081909a683f8c850dcbf9 |
completed | April 29, 2026, 2:43 a.m. |
Created at: April 17, 2026, 3:05 p.m.