Triple
T14794859
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caldas |
E347746
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Marulanda |
E194544
|
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: Marulanda | Statement: [Caldas, hasMunicipality, Marulanda]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marulanda Context triple: [Caldas, hasMunicipality, Marulanda]
-
A.
Marulanda
chosen
Marulanda is a small municipality and town located in the Caldas Department of Colombia, known for its rural Andean landscapes and agricultural economy.
-
B.
Orohena
Orohena is the highest peak on the island of Tahiti in French Polynesia, known for its rugged volcanic terrain and prominence in the Society Islands.
-
C.
Marmato
Marmato is a historic Colombian mining town in the Caldas Department, renowned for its centuries-old gold extraction and terraced mountainside setting.
-
D.
Iramuco
Iramuco is a town in Mexico known for its cultural and municipal links with international partner cities such as the London Borough of Ealing.
-
E.
Tumbalá
Tumbalá is a municipality in the Mexican state of Chiapas, known for its lush jungle landscapes and proximity to popular natural attractions.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5fdd548190a2ee5e668c2b20b4 |
completed | April 14, 2026, 11:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe389183a881908e6af44b71f81ace |
completed | May 8, 2026, 7:25 p.m. |
Created at: April 10, 2026, 1:31 a.m.