Triple
T15722726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sagay |
E381139
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
Maquiling
Maquiling is a barangay (village-level administrative division) within the city of Sagay in the Philippines.
|
E1173276
|
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: Maquiling | Statement: [Sagay, hasBarangay, Maquiling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Maquiling Context triple: [Sagay, hasBarangay, Maquiling]
-
A.
Maragondon
Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
-
B.
Malibcong
Malibcong is a remote, mountainous municipality in the Philippine province of Abra known for its indigenous communities and largely undeveloped natural landscapes.
-
C.
Tagoloan
Tagoloan is a coastal municipality in Misamis Oriental, Philippines, known for its strategic location near Cagayan de Oro and its growing industrial and port activities.
-
D.
Mamanguape
Mamanguape is a municipality in the Brazilian state of Paraíba, known for its historical colonial architecture and location near the Mamanguape River on the state’s northern coast.
-
E.
Palawano
Palawano is an Austronesian language spoken by the indigenous Palawano people of Palawan in the Philippines.
- 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: Maquiling Triple: [Sagay, hasBarangay, Maquiling]
Generated description
Maquiling is a barangay (village-level administrative division) within the city of Sagay in the Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Maquiling Target entity description: Maquiling is a barangay (village-level administrative division) within the city of Sagay in the Philippines.
-
A.
Maragondon
Maragondon is a historic rural municipality in the province of Cavite in the Philippines, known for its Spanish-era heritage sites and nearby natural attractions.
-
B.
Malibcong
Malibcong is a remote, mountainous municipality in the Philippine province of Abra known for its indigenous communities and largely undeveloped natural landscapes.
-
C.
Tagoloan
Tagoloan is a coastal municipality in Misamis Oriental, Philippines, known for its strategic location near Cagayan de Oro and its growing industrial and port activities.
-
D.
Mamanguape
Mamanguape is a municipality in the Brazilian state of Paraíba, known for its historical colonial architecture and location near the Mamanguape River on the state’s northern coast.
-
E.
Palawano
Palawano is an Austronesian language spoken by the indigenous Palawano people of Palawan in the Philippines.
- 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fb1fdd4819088f3e243263e5f73 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82f68bf881909e5ad8a6ab81684a |
completed | May 9, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_69ff8388b3588190ae55c123bb19cb2c |
completed | May 9, 2026, 6:57 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff84125e808190a4d465d9effad639 |
completed | May 9, 2026, 6:59 p.m. |
Created at: April 10, 2026, 4:45 a.m.