Triple
T17722721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Department |
E442381
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object | Luque |
—
|
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: Luque | Statement: [Central Department, hasCity, Luque]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Luque Context triple: [Central Department, hasCity, Luque]
-
A.
Luque
chosen
Luque is a city in Paraguay, part of the Greater Asunción metropolitan area and known for its proximity to the country’s main international airport.
-
B.
San Justo
San Justo is a city in the Buenos Aires Province of Argentina, forming part of the Greater Buenos Aires metropolitan area.
-
C.
Gualeguaychú
Gualeguaychú is a city in eastern Argentina known for its vibrant Carnival celebrations and riverside tourism.
-
D.
Ciudad Mendoza
Ciudad Mendoza is a small city in the state of Veracruz, Mexico, known for its location in the mountainous central region near key transport routes.
-
E.
Río Cuarto
Río Cuarto is a major city in central Argentina known as an important commercial, agricultural, and educational hub within Córdoba Province.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47487b4988190b14237a4e6376e9a |
completed | April 19, 2026, 6:21 a.m. |
Created at: April 10, 2026, 10:07 a.m.