Triple
T12223368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Catarina |
E291275
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Lages
Lages is a city in southern Brazil known for its cattle ranching heritage and cool, highland climate.
|
E968470
|
NE FINISHED |
How this triple was built (4 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: Lages | Statement: [Santa Catarina, hasCity, Lages]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lages Context triple: [Santa Catarina, hasCity, Lages]
-
A.
Lerse
Lerse is a supporting character in Johann Wolfgang von Goethe’s play "Götz von Berlichingen," known as a loyal and brave follower of the titular knight.
-
B.
Diass
Diass is a commune in western Senegal that hosts the country’s main international gateway, Blaise Diagne International Airport.
-
C.
Lugos
Lugos is a town in present-day Romania, historically part of the Austro-Hungarian Empire, known as the birthplace of actor Bela Lugosi.
-
D.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
E.
Lasne
Lasne is a picturesque, affluent municipality in Walloon Brabant, Belgium, known for its rural character and high quality of life.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Lages Triple: [Santa Catarina, hasCity, Lages]
Generated description
Lages is a city in southern Brazil known for its cattle ranching heritage and cool, highland climate.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lages Target entity description: Lages is a city in southern Brazil known for its cattle ranching heritage and cool, highland climate.
-
A.
Lerse
Lerse is a supporting character in Johann Wolfgang von Goethe’s play "Götz von Berlichingen," known as a loyal and brave follower of the titular knight.
-
B.
Diass
Diass is a commune in western Senegal that hosts the country’s main international gateway, Blaise Diagne International Airport.
-
C.
Lugos
Lugos is a town in present-day Romania, historically part of the Austro-Hungarian Empire, known as the birthplace of actor Bela Lugosi.
-
D.
Luga
Luga is a small historic town in northwestern Russia known for its strategic location and role in regional transport and industry.
-
E.
Lasne
Lasne is a picturesque, affluent municipality in Walloon Brabant, Belgium, known for its rural character and high quality of life.
- F. None of above. chosen
Provenance (5 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_69d6ab668acc8190963ba424049d6aee |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91ca11f788190bad2efb6c83ffccb |
completed | April 10, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f60aa6d3d481909852a6f2f90d7a41 |
completed | May 2, 2026, 2:31 p.m. |
| NEDg | Description generation | batch_69f60c06e4c08190985114da9317e8fd |
completed | May 2, 2026, 2:36 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f60c97a7e08190b782b3aa6d60d770 |
completed | May 2, 2026, 2:39 p.m. |
Created at: April 8, 2026, 9:51 p.m.