Triple
T14502340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Albay |
E340173
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Guinobatan
Guinobatan is a municipality in the province of Albay in the Bicol Region of the Philippines, known for its rural landscapes and proximity to Mayon Volcano.
|
E1102626
|
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: Guinobatan | Statement: [Albay, hasMunicipality, Guinobatan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guinobatan Context triple: [Albay, hasMunicipality, Guinobatan]
-
A.
Malbago
Malbago is a coastal barangay in the municipality of Daanbantayan in northern Cebu, Philippines.
-
B.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
-
C.
Maljamar
Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
-
D.
Guinsiliban
Guinsiliban is a coastal municipality on the island-province of Camiguin in the Philippines, known for its rural communities and proximity to volcanic landscapes and marine attractions.
-
E.
Tinogasta
Tinogasta is a town in northwestern Argentina known for its wine production, hot springs, and location along the Andean mountain routes in Catamarca Province.
- 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: Guinobatan Triple: [Albay, hasMunicipality, Guinobatan]
Generated description
Guinobatan is a municipality in the province of Albay in the Bicol Region of the Philippines, known for its rural landscapes and proximity to Mayon Volcano.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Guinobatan Target entity description: Guinobatan is a municipality in the province of Albay in the Bicol Region of the Philippines, known for its rural landscapes and proximity to Mayon Volcano.
-
A.
Malbago
Malbago is a coastal barangay in the municipality of Daanbantayan in northern Cebu, Philippines.
-
B.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
-
C.
Maljamar
Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
-
D.
Guinsiliban
Guinsiliban is a coastal municipality on the island-province of Camiguin in the Philippines, known for its rural communities and proximity to volcanic landscapes and marine attractions.
-
E.
Tinogasta
Tinogasta is a town in northwestern Argentina known for its wine production, hot springs, and location along the Andean mountain routes in Catamarca Province.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e0f9048190a2d266cfa4f9dfb6 |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9b6f7481908b7eb76226a93545 |
completed | May 8, 2026, 4:59 a.m. |
| NEDg | Description generation | batch_69fd6efed3108190a524c64adf740303 |
completed | May 8, 2026, 5:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd6f8648408190aed910a7f269abee |
completed | May 8, 2026, 5:07 a.m. |
Created at: April 10, 2026, 1:21 a.m.