Triple
T7916736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Quimbo Dam |
E183845
|
entity |
| Predicate | operator |
P179
|
FINISHED |
| Object | Emgesa |
E699864
|
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: Emgesa | Statement: [El Quimbo Dam, operator, Emgesa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Emgesa Context triple: [El Quimbo Dam, operator, Emgesa]
-
A.
Emgesa
chosen
Emgesa is an energy company that operates hydroelectric power facilities in Colombia.
-
B.
Lanseria
Lanseria is a town in the northwestern part of Johannesburg, South Africa, known primarily for hosting the privately owned Lanseria International Airport.
-
C.
Ruimsig
Ruimsig is a suburban residential area in Roodepoort, west of Johannesburg, known for its golf course, botanical gardens, and family-oriented lifestyle.
-
D.
Nongoma
Nongoma is a town in KwaZulu-Natal, South Africa, historically significant as a center of Zulu royalty and traditional leadership.
-
E.
Gingolx
Gingolx is a remote Nisga’a First Nation village on British Columbia’s northwest coast, known for its rich Indigenous culture, fishing traditions, and scenic coastal and river landscapes.
- 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_69ca828efbe48190bd48482650182e79 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a8e8b388190b5544eb5b8159e07 |
completed | March 31, 2026, 3:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc563cb0a081909ed43ff45a8a1fa0 |
completed | March 31, 2026, 11:18 p.m. |
Created at: March 30, 2026, 5:05 p.m.