Triple
T1326464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paraguay |
E28339
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Asunción |
E98396
|
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: Asunción | Statement: [Paraguay, capital, Asunción]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Asunción Context triple: [Paraguay, capital, Asunción]
-
A.
Asunción
chosen
Asunción is the capital and largest city of Paraguay, located along the Paraguay River and serving as the country’s main political, cultural, and economic center.
-
B.
Asuncion
Asuncion is a remote volcanic island in the Northern Mariana Islands, known for its steep stratovolcano and relatively undisturbed natural environment.
-
C.
Ciudad del Este
Ciudad del Este is a major commercial city in eastern Paraguay, known as a busy border trading hub near the tri-border area with Brazil and Argentina.
-
D.
Montevideo
Montevideo is the capital and largest city of Uruguay, serving as the country’s main political, economic, and cultural center.
-
E.
Santa Cruz de la Sierra
Santa Cruz de la Sierra is Bolivia’s largest and most populous city, a major economic hub in the country’s eastern lowlands known for its rapid growth and vibrant commercial activity.
- 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_69a498540a2481909e807a762280d3ba |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1c0a22881909eff0fc6c91a5f41 |
completed | March 1, 2026, 10:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acc62764d88190b7d1fca10835f560 |
completed | March 8, 2026, 12:43 a.m. |
Created at: March 1, 2026, 7:55 p.m.