Triple
T21175239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lima Metro |
E521794
|
entity |
| Predicate | serves |
P98
|
FINISHED |
| Object | Callao |
—
|
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: Callao | Statement: [Lima Metro, serves, Callao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Callao Context triple: [Lima Metro, serves, Callao]
-
A.
Callao
chosen
Callao is Peru’s chief seaport and a major coastal city adjacent to Lima, serving as the country’s principal gateway for maritime trade.
-
B.
Callao
Callao is a central Madrid Metro station located in the busy commercial and entertainment hub around Plaza del Callao in the city center.
-
C.
Callao
Callao is a small unincorporated community in Northumberland County, Virginia, known primarily as a rural locality in the Northern Neck region of the state.
-
D.
Lima
Lima is the capital and largest city of Peru, known as a major political, economic, and cultural center on South America's Pacific coast.
-
E.
Lima
Lima is a station on Buenos Aires’ historic Underground Line A, serving passengers in the city’s central area.
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7271597288190b04baff9ca8d866c |
completed | April 21, 2026, 7:28 a.m. |
Created at: April 16, 2026, 3 p.m.