Triple
T21348410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Olango Island |
E526404
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
Sabang
Sabang is a coastal barangay on Olango Island in the Philippines, known for its fishing community and proximity to local marine and bird sanctuaries.
|
E1478797
|
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: Sabang | Statement: [Olango Island, hasBarangay, Sabang]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sabang Context triple: [Olango Island, hasBarangay, Sabang]
-
A.
Sabang
Sabang is a coastal barangay in Baler, Aurora, Philippines, known for its surfing beaches and tourism.
-
B.
Sabang
Sabang is a small Indonesian city and popular tourist destination located on Weh Island off the northern tip of Sumatra.
-
C.
Sabang
Sabang is a barangay (village-level administrative division) located in the municipality of Morong in the province of Bataan, Philippines.
-
D.
Banda Aceh
Banda Aceh is the largest city in Indonesia’s Aceh province, known as a historic center of Islamic culture and for being one of the areas hardest hit by the 2004 Indian Ocean tsunami.
-
E.
Labuan
Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
- 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: Sabang Triple: [Olango Island, hasBarangay, Sabang]
Generated description
Sabang is a coastal barangay on Olango Island in the Philippines, known for its fishing community and proximity to local marine and bird sanctuaries.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sabang Target entity description: Sabang is a coastal barangay on Olango Island in the Philippines, known for its fishing community and proximity to local marine and bird sanctuaries.
-
A.
Sabang
Sabang is a coastal barangay in Baler, Aurora, Philippines, known for its surfing beaches and tourism.
-
B.
Sabang
Sabang is a barangay (village-level administrative division) located in the municipality of Morong in the province of Bataan, Philippines.
-
C.
Sabang
Sabang is a small Indonesian city and popular tourist destination located on Weh Island off the northern tip of Sumatra.
-
D.
Banda Aceh
Banda Aceh is the largest city in Indonesia’s Aceh province, known as a historic center of Islamic culture and for being one of the areas hardest hit by the 2004 Indian Ocean tsunami.
-
E.
Labuan
Labuan is a coastal town in Banten, western Java, Indonesia, known as a gateway to nearby natural attractions and marine tourism areas.
- 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_69e0b51cd5cc81909ac1187971e8a8ad |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5baab4e081908916a289c607cf3a |
completed | April 26, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a09a5cc48508190a40802e681430eae |
completed | May 17, 2026, 11:26 a.m. |
| NEDg | Description generation | batch_6a09a778a998819092eeb83ec1f5aed1 |
completed | May 17, 2026, 11:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a09a7bcd5188190be3009fb3bd00af6 |
completed | May 17, 2026, 11:34 a.m. |
Created at: April 16, 2026, 5:01 p.m.