Triple
T9652625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Leyte |
E233372
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Macrohon
Macrohon is a coastal municipality in the province of Southern Leyte in the Philippines, known for its beaches and rural communities.
|
E811956
|
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: Macrohon | Statement: [Southern Leyte, hasMunicipality, Macrohon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Macrohon Context triple: [Southern Leyte, hasMunicipality, Macrohon]
-
A.
Marcoola
Marcoola is a coastal suburb on Queensland’s Sunshine Coast in Australia, known for its beaches and as the location of the region’s main airport.
-
B.
Mighty Barrolle
Mighty Barrolle is a prominent Liberian football club known for its historic success and strong fan base in the Liberian Premier League.
-
C.
Gigante
Gigante is a municipality and town located in the Huila Department of southwestern Colombia, known for its agricultural activities and Andean landscapes.
-
D.
Mighty Mo
Mighty Mo is the famous nickname of the USS Missouri, a U.S. Navy battleship best known as the site of Japan’s formal surrender in World War II.
-
E.
Pagalu
Pagalu is an alternative name for Annobón, a small volcanic island in the Gulf of Guinea that belongs to Equatorial Guinea.
- 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: Macrohon Triple: [Southern Leyte, hasMunicipality, Macrohon]
Generated description
Macrohon is a coastal municipality in the province of Southern Leyte in the Philippines, known for its beaches and rural communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Macrohon Target entity description: Macrohon is a coastal municipality in the province of Southern Leyte in the Philippines, known for its beaches and rural communities.
-
A.
Marcoola
Marcoola is a coastal suburb on Queensland’s Sunshine Coast in Australia, known for its beaches and as the location of the region’s main airport.
-
B.
Mighty Barrolle
Mighty Barrolle is a prominent Liberian football club known for its historic success and strong fan base in the Liberian Premier League.
-
C.
Gigante
Gigante is a municipality and town located in the Huila Department of southwestern Colombia, known for its agricultural activities and Andean landscapes.
-
D.
Mighty Mo
Mighty Mo is the famous nickname of the USS Missouri, a U.S. Navy battleship best known as the site of Japan’s formal surrender in World War II.
-
E.
Pagalu
Pagalu is an alternative name for Annobón, a small volcanic island in the Gulf of Guinea that belongs to Equatorial Guinea.
- 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_69ca848b31648190b57aa55da20285be |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bb26b748190bc32e2003829b0ec |
completed | April 1, 2026, 10:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1826c91388190b82112c2ca1eae7e |
completed | April 4, 2026, 9:28 p.m. |
| NEDg | Description generation | batch_69d1836d683081908bccf970e4b0980b |
completed | April 4, 2026, 9:32 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d18412c4a08190bce431235e1102fc |
completed | April 4, 2026, 9:35 p.m. |
Created at: March 30, 2026, 8:13 p.m.