Triple
T28128776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruta Nacional 157 |
E711002
|
entity |
| Predicate | connectsKeyCities |
P94566
|
FINISHED |
| Object | cities in Tucumán Province |
—
|
LITERAL 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: cities in Tucumán Province | Statement: [Ruta Nacional 157, connectsKeyCities, cities in Tucumán Province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsKeyCities Context triple: [Ruta Nacional 157, connectsKeyCities, cities in Tucumán Province]
-
A.
connectsMajorCity
Indicates that one entity serves as a link or route providing direct connection to a major city.
-
B.
connectsLargestCitiesOf
chosen
Indicates a relationship where something (typically a route, network, or infrastructure) links together the largest cities within a specified region or set.
-
C.
connectsCity
Indicates a relationship where one entity serves as a link or route that joins or provides direct access between two cities.
-
D.
connectsTypeOfCity
Indicates a relationship where one entity is linked to another as a specific type or category of city.
-
E.
connectsBorderCities
Indicates a relationship where a route, infrastructure, or boundary directly links two or more cities that lie on or near a shared border.
- F. None of above.
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_69ef9b73bd288190a21ae3d6aa14f386 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: April 27, 2026, 9:21 p.m.