Triple
T16979134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Ignacia |
E411894
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
Pilpila
Pilpila is a barangay (village-level administrative division) within the municipality of Santa Ignacia in the Philippines.
|
E1243526
|
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: Pilpila | Statement: [Santa Ignacia, hasBarangay, Pilpila]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pilpila Context triple: [Santa Ignacia, hasBarangay, Pilpila]
-
A.
Pilcaniyeu
Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
-
B.
Pocito
Pocito is a city in western Argentina known for its agricultural production, particularly vineyards and wineries, within San Juan Province.
-
C.
Piripiri
Piripiri is a municipality in the Brazilian state of Piauí, known for its regional commerce and proximity to natural attractions such as the Sete Cidades National Park.
-
D.
Pitalito
Pitalito is a major town and coffee-producing hub in southern Colombia, known as one of the country’s most important centers for high-quality coffee.
-
E.
Pintuyan
Pintuyan is a coastal municipality in the province of Southern Leyte in the Philippines, known for its marine biodiversity and whale shark watching.
- 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: Pilpila Triple: [Santa Ignacia, hasBarangay, Pilpila]
Generated description
Pilpila is a barangay (village-level administrative division) within the municipality of Santa Ignacia in the Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pilpila Target entity description: Pilpila is a barangay (village-level administrative division) within the municipality of Santa Ignacia in the Philippines.
-
A.
Pilcaniyeu
Pilcaniyeu is a small town in Argentina’s Patagonia region, located in the Andean area of Río Negro Province and known for its rural character and nearby natural landscapes.
-
B.
Pocito
Pocito is a city in western Argentina known for its agricultural production, particularly vineyards and wineries, within San Juan Province.
-
C.
Piripiri
Piripiri is a municipality in the Brazilian state of Piauí, known for its regional commerce and proximity to natural attractions such as the Sete Cidades National Park.
-
D.
Pitalito
Pitalito is a major town and coffee-producing hub in southern Colombia, known as one of the country’s most important centers for high-quality coffee.
-
E.
Pintuyan
Pintuyan is a coastal municipality in the province of Southern Leyte in the Philippines, known for its marine biodiversity and whale shark watching.
- 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_69d886ca8f348190812768ea8d5055ce |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d185a9408190a991bf8a1ef694f0 |
completed | April 18, 2026, 6:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00d477f7ec81909f1f0243004c9050 |
completed | May 10, 2026, 6:54 p.m. |
| NEDg | Description generation | batch_6a00d5503be88190ac15a327ff3782ec |
completed | May 10, 2026, 6:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d66e450c8190ae0befd3d7875ed8 |
completed | May 10, 2026, 7:03 p.m. |
Created at: April 10, 2026, 5:32 a.m.