Triple
T21052233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lima Metro Line 1 |
E518615
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object | Cabitos station |
—
|
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: Cabitos station | Statement: [Lima Metro Line 1, hasStation, Cabitos station]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cabitos station Context triple: [Lima Metro Line 1, hasStation, Cabitos station]
-
A.
Cabitos station
chosen
Cabitos station is a stop on Lima Metro’s Line 1 serving passengers in the southern part of Peru’s capital city.
-
B.
Propatria station
Propatria station is a major Caracas Metro station in Venezuela that serves as the western terminus of Line 1.
-
C.
Paniqui station
Paniqui station is a railway stop serving the municipality of Paniqui in the province of Tarlac in the Philippines.
-
D.
Legarda station
Legarda station is an elevated rapid transit stop on Manila’s LRT Line 2 serving the Sampaloc area and nearby universities.
-
E.
Recto station
Recto station is an elevated terminal station of Manila’s LRT Line 2 located in the busy commercial district of Recto Avenue in the Philippines.
- 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_69e0b5053ac48190921529544959e906 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fd7cabe881909e6b258a14d501a6 |
completed | April 21, 2026, 4:30 a.m. |
Created at: April 16, 2026, 2:35 p.m.