Triple
T20357401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lääne-Viru County |
E496685
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Tapa |
—
|
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: Tapa | Statement: [Lääne-Viru County, contains, Tapa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tapa Context triple: [Lääne-Viru County, contains, Tapa]
-
A.
Tapa
chosen
Tapa is a town in northern Estonia that serves as a key railway junction and transport hub in the country’s rail network.
-
B.
Tapa
Tapa is an ethnic group in central Nigeria, more commonly known as the Nupe people, recognized for their rich cultural traditions, crafts, and historical kingdom along the Niger River.
-
C.
Tapukara
Tapukara is an emerging industrial town in Rajasthan, India, known for its manufacturing hubs and growing economic activity.
-
D.
Tapalpa
Tapalpa is a picturesque mountain town in the Mexican state of Jalisco, known for its colonial architecture, pine forests, and outdoor recreation.
-
E.
Tappara
Tappara is a prominent professional ice hockey club from Tampere, Finland, known as one of the most successful and historic teams in the Finnish Liiga.
- 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_69e0b4a3f7f48190b37f354574028ca6 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67854c0448190ab10363f8a218afb |
completed | April 20, 2026, 7:02 p.m. |
Created at: April 16, 2026, 11:25 a.m.