Triple
T910970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lombardy |
E19656
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Como |
E81378
|
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: Como | Statement: [Lombardy, hasMajorCity, Como]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Como Context triple: [Lombardy, hasMajorCity, Como]
-
A.
Como
chosen
Como is a historic city in northern Italy near the Swiss border, known for its scenic setting at the southern tip of Lake Como and its medieval architecture, including the Como Cathedral.
-
B.
American River
The American River is a major waterway in Northern California known for its role in the Gold Rush, outdoor recreation, and as a key tributary of the Sacramento River.
-
C.
Amer River
The Amer River is a waterway in the southern Netherlands that flows through the Biesbosch wetlands and connects to major Dutch river and canal systems.
-
D.
Columbia
Columbia was the former name of the John F. Kennedy/University of Massachusetts Boston subway station on Boston’s MBTA Red Line.
-
E.
Columbia
Columbia is an outdoor apparel and footwear brand known for its durable, weather-resistant gear for activities like hiking, skiing, and camping.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2de5b008190851852331db41324 |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ada9536bec8190acf50065863bd16a |
completed | March 8, 2026, 4:52 p.m. |
Created at: March 1, 2026, 7:39 p.m.