Triple
T16469353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Paz Department |
E400018
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Mercedes La Ceiba
Mercedes La Ceiba is a municipality located in the La Paz Department of Honduras.
|
E1215419
|
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: Mercedes La Ceiba | Statement: [La Paz Department, hasMunicipality, Mercedes La Ceiba]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mercedes La Ceiba Context triple: [La Paz Department, hasMunicipality, Mercedes La Ceiba]
-
A.
Cambadélis
Cambadélis is the surname of Jean-Christophe Cambadélis, a French politician and former First Secretary of the Socialist Party.
-
B.
Salcedo
Salcedo is a coastal municipality in the province of Eastern Samar in the Philippines, known for its fishing communities and rural landscapes.
-
C.
Salcedo
Salcedo is a rural municipality in the province of Ilocos Sur in the Philippines, known for its agricultural communities and mountainous landscapes.
-
D.
Salcedo
Salcedo is a town in Ecuador’s Cotopaxi Province known as a gateway to the remote Llanganates National Park and for its traditional Andean culture.
-
E.
Caibarién
Caibarién is a coastal town and municipality in central Cuba known historically for its fishing industry and nearby keys.
- 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: Mercedes La Ceiba Triple: [La Paz Department, hasMunicipality, Mercedes La Ceiba]
Generated description
Mercedes La Ceiba is a municipality located in the La Paz Department of Honduras.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mercedes La Ceiba Target entity description: Mercedes La Ceiba is a municipality located in the La Paz Department of Honduras.
-
A.
Cambadélis
Cambadélis is the surname of Jean-Christophe Cambadélis, a French politician and former First Secretary of the Socialist Party.
-
B.
Salcedo
Salcedo is a coastal municipality in the province of Eastern Samar in the Philippines, known for its fishing communities and rural landscapes.
-
C.
Salcedo
Salcedo is a rural municipality in the province of Ilocos Sur in the Philippines, known for its agricultural communities and mountainous landscapes.
-
D.
Salcedo
Salcedo is a town in Ecuador’s Cotopaxi Province known as a gateway to the remote Llanganates National Park and for its traditional Andean culture.
-
E.
Caibarién
Caibarién is a coastal town and municipality in central Cuba known historically for its fishing industry and nearby keys.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dcfed6c8190b8dbe4b65b0ab817 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f5af4308190bd023624de35027f |
completed | May 10, 2026, 9:26 a.m. |
| NEDg | Description generation | batch_6a0050c5d4548190a674c1c19f08a9fd |
completed | May 10, 2026, 9:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0051a7ae208190b33d42cc8d4bb21f |
completed | May 10, 2026, 9:36 a.m. |
Created at: April 10, 2026, 5:11 a.m.