Triple
T8376563
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buenos Aires Underground Line A |
E197590
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Pasco
Pasco is a station on Buenos Aires’ historic Line A subway, serving the Balvanera neighborhood in Argentina’s capital.
|
E729747
|
NE FINISHED |
How this triple was built (4 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: Pasco | Statement: [Buenos Aires Underground Line A, hasStation, Pasco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasco Context triple: [Buenos Aires Underground Line A, hasStation, Pasco]
-
A.
Pasco
Pasco is a city in southeastern Washington State that forms part of the Tri-Cities region along with Kennewick and Richland.
-
B.
Eustis
Eustis is a surname of English origin borne by various notable individuals, including military figures and public officials in American history.
-
C.
Lakeland
Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
-
D.
Bartow
Bartow is a small city in central Florida that serves as the county seat of Polk County and a regional hub for government and commerce.
-
E.
Bradenton
Bradenton is a city on Florida’s Gulf Coast known for its waterfront location along the Manatee River and proximity to popular beaches and the Sarasota–Bradenton metropolitan area.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Pasco Triple: [Buenos Aires Underground Line A, hasStation, Pasco]
Generated description
Pasco is a station on Buenos Aires’ historic Line A subway, serving the Balvanera neighborhood in Argentina’s capital.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pasco Target entity description: Pasco is a station on Buenos Aires’ historic Line A subway, serving the Balvanera neighborhood in Argentina’s capital.
-
A.
Pasco
Pasco is a city in southeastern Washington State that forms part of the Tri-Cities region along with Kennewick and Richland.
-
B.
Eustis
Eustis is a surname of English origin borne by various notable individuals, including military figures and public officials in American history.
-
C.
Lakeland
Lakeland is a residential neighborhood located within the city of College Park in Prince George's County, Maryland.
-
D.
Bartow
Bartow is a small city in central Florida that serves as the county seat of Polk County and a regional hub for government and commerce.
-
E.
Bradenton
Bradenton is a city on Florida’s Gulf Coast known for its waterfront location along the Manatee River and proximity to popular beaches and the Sarasota–Bradenton metropolitan area.
- F. None of above. chosen
Provenance (5 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_69ca82f64c188190af4e1608036b865d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb80c094908190afe9cc54ce4f4d58 |
completed | March 31, 2026, 8:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cde7f19ba08190a08cf5aea522c021 |
completed | April 2, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_69cdebf944008190b7e758ac59257e22 |
completed | April 2, 2026, 4:09 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cdeccedf4081909cab853ee1ff1b82 |
completed | April 2, 2026, 4:13 a.m. |
Created at: March 30, 2026, 6:01 p.m.