Triple
T4536721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Makati |
E107424
|
entity |
| Predicate | hasDistrict |
P459
|
FINISHED |
| Object |
Urdaneta
Urdaneta is an upscale residential and commercial barangay in Makati, Metro Manila, known for its affluent neighborhoods and proximity to the city’s central business district.
|
E450364
|
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: Urdaneta | Statement: [Makati, hasDistrict, Urdaneta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Urdaneta Context triple: [Makati, hasDistrict, Urdaneta]
-
A.
Danao
Danao is a coastal city and municipality on Cebu Island in the Philippines known for its historical significance and local industries.
-
B.
Plaridel
Plaridel is a municipality in the province of Bulacan in the Philippines, known for its historical significance and proximity to Metro Manila.
-
C.
San Teodoro
San Teodoro is a popular coastal resort town in northeastern Sardinia, Italy, known for its white-sand beaches and vibrant summer tourism.
-
D.
Dalaguete
Dalaguete is a coastal municipality in the province of Cebu in the Philippines, known for its cool highland areas and vegetable farming.
-
E.
San Miguel
San Miguel is a coastal district of Lima, Peru, known for its residential areas, shopping centers, and access to major avenues and the Pacific shoreline.
- 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: Urdaneta Triple: [Makati, hasDistrict, Urdaneta]
Generated description
Urdaneta is an upscale residential and commercial barangay in Makati, Metro Manila, known for its affluent neighborhoods and proximity to the city’s central business district.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Urdaneta Target entity description: Urdaneta is an upscale residential and commercial barangay in Makati, Metro Manila, known for its affluent neighborhoods and proximity to the city’s central business district.
-
A.
Danao
Danao is a coastal city and municipality on Cebu Island in the Philippines known for its historical significance and local industries.
-
B.
Plaridel
Plaridel is a municipality in the province of Bulacan in the Philippines, known for its historical significance and proximity to Metro Manila.
-
C.
San Teodoro
San Teodoro is a popular coastal resort town in northeastern Sardinia, Italy, known for its white-sand beaches and vibrant summer tourism.
-
D.
Dalaguete
Dalaguete is a coastal municipality in the province of Cebu in the Philippines, known for its cool highland areas and vegetable farming.
-
E.
San Miguel
San Miguel is a coastal district of Lima, Peru, known for its residential areas, shopping centers, and access to major avenues and the Pacific shoreline.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b78b8481909d79131723d4be22 |
completed | March 20, 2026, 2:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdacf5858081909d38cad86d4014f2 |
completed | March 20, 2026, 8:24 p.m. |
| NEDg | Description generation | batch_69bdad97c9e0819093849c81fb2a3d8c |
completed | March 20, 2026, 8:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bdae2dd51081909a24017a4b983f70 |
completed | March 20, 2026, 8:29 p.m. |
Created at: March 20, 2026, 1:04 p.m.