Triple
T16536917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sud Yungas Province |
E401715
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object |
Chulumani
Chulumani is a small town in Bolivia’s Yungas region known for its subtropical climate, coffee and coca production, and role as a gateway to scenic mountain and cloud-forest landscapes.
|
E1220277
|
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: Chulumani | Statement: [Sud Yungas Province, capital, Chulumani]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chulumani Context triple: [Sud Yungas Province, capital, Chulumani]
-
A.
Ahangama
Ahangama is a coastal town in southern Sri Lanka known for its beaches, surfing spots, and traditional stilt fishermen.
-
B.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
C.
Yunguyo
Yunguyo is a Peruvian town situated on the shores of Lake Titicaca near the border with Bolivia.
-
D.
Mangini
Mangini is an Italian surname most notably associated with former NFL head coach and analyst Eric Mangini.
-
E.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
- 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: Chulumani Triple: [Sud Yungas Province, capital, Chulumani]
Generated description
Chulumani is a small town in Bolivia’s Yungas region known for its subtropical climate, coffee and coca production, and role as a gateway to scenic mountain and cloud-forest landscapes.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chulumani Target entity description: Chulumani is a small town in Bolivia’s Yungas region known for its subtropical climate, coffee and coca production, and role as a gateway to scenic mountain and cloud-forest landscapes.
-
A.
Ahangama
Ahangama is a coastal town in southern Sri Lanka known for its beaches, surfing spots, and traditional stilt fishermen.
-
B.
Kasangati
Kasangati is a town in central Uganda that serves as a growing commercial and residential hub within the Greater Kampala metropolitan area.
-
C.
Yunguyo
Yunguyo is a Peruvian town situated on the shores of Lake Titicaca near the border with Bolivia.
-
D.
Mangini
Mangini is an Italian surname most notably associated with former NFL head coach and analyst Eric Mangini.
-
E.
Marangona
Marangona is the largest and most famous bell of St Mark's Campanile in Venice, traditionally used to mark the beginning and end of the working day and to signal important civic events.
- 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_69d88384bc30819084229e7dcdc39a41 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e34558ec448190a6dcc15d62d1889c |
completed | April 18, 2026, 8:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0067aafee48190a0652fb4fac04a5b |
completed | May 10, 2026, 11:10 a.m. |
| NEDg | Description generation | batch_6a00686f87408190b7d8a41cd54735d8 |
completed | May 10, 2026, 11:13 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a006b6edd7081908730363b267253dd |
completed | May 10, 2026, 11:26 a.m. |
Created at: April 10, 2026, 5:15 a.m.