Triple
T22374539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TJ Holowaychuk |
E553120
|
entity |
| Predicate | created |
P538
|
FINISHED |
| Object | Express |
—
|
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: Express | Statement: [TJ Holowaychuk, created, Express]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Express Context triple: [TJ Holowaychuk, created, Express]
-
A.
Express
Express is the nickname of the Windsor Express, a professional basketball team based in Windsor, Ontario, Canada.
-
B.
Express
"Express" is a popular song from the film and stage musical "Burlesque," known for its sultry style and association with Christina Aguilera’s performance.
-
C.
Express
Express is an American fashion retailer known for its trendy, youth-oriented apparel and accessories sold through mall-based stores and online.
-
D.
Express
chosen
Express is a minimalist and flexible web application framework for Node.js, widely used for building APIs and server-side applications.
-
E.
Express
Express is a category of fast passenger train service operated by Czech Railways, providing quicker long-distance connections with limited stops across the Czech rail network.
- 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_69e11e4c03248190a26a5060ea6973ee |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15806b534819083716c2b090ede42 |
completed | April 29, 2026, 12:59 a.m. |
Created at: April 16, 2026, 8:45 p.m.