Triple
T17106546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Merval |
E415112
|
entity |
| Predicate | hasRouteTerminus |
P39212
|
FINISHED |
| Object | Puerto station |
E415113
|
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: Puerto station | Statement: [Merval, hasRouteTerminus, Puerto station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Puerto station Context triple: [Merval, hasRouteTerminus, Puerto station]
-
A.
Puerto station
chosen
Puerto station is the central waterfront terminus of the Valparaíso Metro in Valparaíso, Chile, serving as a key access point to the historic port city center.
-
B.
Barrancas station
Barrancas station is a stop on Santiago, Chile’s Metro system, serving Line 5 in the western part of the city.
-
C.
San Pedro station
San Pedro station is a railway stop on the Philippine National Railways’ Metro Commuter Line serving the city of San Pedro in Laguna, Philippines.
-
D.
Portales station
Portales station is a stop on the Valparaíso Metro system in Chile, serving passengers along the coastal urban corridor of the Valparaíso metropolitan area.
-
E.
Saenz Peña station
Saenz Peña station is a stop on Line A of the Buenos Aires Underground, serving passengers in the central area of Argentina’s capital city.
- 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_69d886cfc8e88190b05ba466edd35591 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dc2750b481908de18e8cb8f2195c |
completed | April 18, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a013a019540819083ce6100b24f8cfb |
completed | May 11, 2026, 2:08 a.m. |
Created at: April 10, 2026, 5:35 a.m.