Triple
T17106583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puerto station |
E415113
|
entity |
| Predicate | connectsTo |
P845
|
FINISHED |
| Object | Barón station |
E415114
|
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: Barón station | Statement: [Puerto station, connectsTo, Barón station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barón station Context triple: [Puerto station, connectsTo, Barón station]
-
A.
Barón station
chosen
Barón station is a passenger rail stop on the Valparaíso Metro system in Valparaíso, Chile, serving the coastal urban area.
-
B.
Belen station
Belen station is a commuter rail station in Belen, New Mexico, serving as a key stop on the New Mexico Rail Runner Express line.
-
C.
Primos station
Primos station is a commuter rail stop in Pennsylvania serving the SEPTA Regional Rail network.
-
D.
Miltenberg station
Miltenberg station is the main railway station serving the town of Miltenberg in Bavaria, Germany, providing regional rail connections along the Main River.
-
E.
Torrassa station
Torrassa station is an underground rapid transit stop in L'Hospitalet de Llobregat that forms part of Barcelona’s metro network.
- 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.