Triple
T7559101
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sesquilé |
E178748
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object |
Lake Tominé
Lake Tominé is an artificial reservoir in the Colombian Andes, popular for water sports and weekend tourism near Bogotá.
|
E808213
|
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: Lake Tominé | Statement: [Sesquilé, locatedNear, Lake Tominé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lake Tominé Context triple: [Sesquilé, locatedNear, Lake Tominé]
-
A.
Totem Lake
Totem Lake is a commercial and residential neighborhood in Kirkland, Washington, known for its major shopping center and medical facilities.
-
B.
Teresa Lake
Teresa Lake is a small alpine glacial lake in Nevada’s Great Basin National Park, known for its scenic mountain setting and hiking access.
-
C.
Simly Lake
Simly Lake is a major freshwater reservoir and popular recreational spot located in the Margalla Hills near Islamabad, Pakistan.
-
D.
Mozingo Lake
Mozingo Lake is a recreational reservoir in northwest Missouri known for fishing, boating, camping, and a surrounding golf course and park facilities.
-
E.
Lac des Minimes
Lac des Minimes is a scenic artificial lake in eastern Paris, popular for boating and leisurely walks within the expansive Bois de Vincennes park.
- 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: Lake Tominé Triple: [Sesquilé, locatedNear, Lake Tominé]
Generated description
Lake Tominé is an artificial reservoir in the Colombian Andes, popular for water sports and weekend tourism near Bogotá.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lake Tominé Target entity description: Lake Tominé is an artificial reservoir in the Colombian Andes, popular for water sports and weekend tourism near Bogotá.
-
A.
Totem Lake
Totem Lake is a commercial and residential neighborhood in Kirkland, Washington, known for its major shopping center and medical facilities.
-
B.
Teresa Lake
Teresa Lake is a small alpine glacial lake in Nevada’s Great Basin National Park, known for its scenic mountain setting and hiking access.
-
C.
Simly Lake
Simly Lake is a major freshwater reservoir and popular recreational spot located in the Margalla Hills near Islamabad, Pakistan.
-
D.
Mozingo Lake
Mozingo Lake is a recreational reservoir in northwest Missouri known for fishing, boating, camping, and a surrounding golf course and park facilities.
-
E.
Lac des Minimes
Lac des Minimes is a scenic artificial lake in eastern Paris, popular for boating and leisurely walks within the expansive Bois de Vincennes park.
- 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_69c69f2da22c8190a50942ac20af70e8 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f8dc7d288190a0d08ba704cc3fc2 |
completed | March 27, 2026, 9:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d160f6855c81909ae0f3f1c041f600 |
completed | April 4, 2026, 7:05 p.m. |
| NEDg | Description generation | batch_69d161c432b08190ba848159cc26a00c |
completed | April 4, 2026, 7:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d162fc597081909a57f842e41b1ad4 |
completed | April 4, 2026, 7:14 p.m. |
Created at: March 27, 2026, 3:50 p.m.