Triple
T7898382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Supertest |
E183387
|
entity |
| Predicate | typicalAssertionLibrary |
P79652
|
FINISHED |
| Object | Chai |
E555968
|
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: Chai | Statement: [Supertest, typicalAssertionLibrary, Chai]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chai Context triple: [Supertest, typicalAssertionLibrary, Chai]
-
A.
Chai
chosen
Chai is a popular JavaScript assertion library commonly used in testing frameworks like Mocha to provide expressive, readable test assertions.
-
B.
Chaiya
Chaiya is an ancient port town in southern Thailand that served as an important regional center and religious hub within the maritime Srivijaya trading network.
-
C.
Tehatta
Tehatta is a town in the Nadia district of the Indian state of West Bengal, known as a local administrative and commercial center for the surrounding rural region.
-
D.
Uji tea
Uji tea is a renowned Japanese green tea celebrated for its high quality and long history of production in the Uji region near Kyoto.
-
E.
Green Tea
"Green Tea" is a gothic short story by Sheridan Le Fanu that follows a clergyman haunted by a demonic monkey, exploring themes of madness, the supernatural, and psychological terror.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a2ae5048190a6824d34b582c366 |
completed | March 31, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bb719a08190a0545a361f559bf7 |
completed | March 31, 2026, 5:29 a.m. |
Created at: March 30, 2026, 5:01 p.m.