Triple
T3138280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Samar |
E65583
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Rosario
Rosario is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
|
E329513
|
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: Rosario | Statement: [Northern Samar, hasMunicipality, Rosario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rosario Context triple: [Northern Samar, hasMunicipality, Rosario]
-
A.
Rosario
Rosario is a major Argentine port city and industrial center located in the province of Santa Fe.
-
B.
Rosario
Rosario is a coastal municipality in the Mexican state of Sinaloa known for its historic architecture, mining heritage, and proximity to the Pacific Ocean.
-
C.
El Rosario
El Rosario is a municipality on the island of Tenerife in Spain’s Canary Islands, known for its coastal landscapes and proximity to the island’s capital, Santa Cruz de Tenerife.
-
D.
El Rosario
El Rosario is a major Mexico City transit hub and neighborhood that serves as a key terminus and interchange point for multiple public transportation lines.
-
E.
De Rosario
De Rosario is the surname of Dwayne De Rosario, a prominent Canadian former professional soccer player known for his goal-scoring and playmaking in Major League Soccer.
- 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: Rosario Triple: [Northern Samar, hasMunicipality, Rosario]
Generated description
Rosario is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rosario Target entity description: Rosario is a coastal municipality in the province of Northern Samar in the Eastern Visayas region of the Philippines.
-
A.
Rosario
Rosario is a major Argentine port city and industrial center located in the province of Santa Fe.
-
B.
Rosario
Rosario is a coastal municipality in the Mexican state of Sinaloa known for its historic architecture, mining heritage, and proximity to the Pacific Ocean.
-
C.
El Rosario
El Rosario is a municipality on the island of Tenerife in Spain’s Canary Islands, known for its coastal landscapes and proximity to the island’s capital, Santa Cruz de Tenerife.
-
D.
El Rosario
El Rosario is a major Mexico City transit hub and neighborhood that serves as a key terminus and interchange point for multiple public transportation lines.
-
E.
De Rosario
De Rosario is the surname of Dwayne De Rosario, a prominent Canadian former professional soccer player known for his goal-scoring and playmaking in Major League Soccer.
- 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_69ad8581c25c8190b0d85ba9b9baa531 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada574509c81908a88bb10ea35516d |
completed | March 8, 2026, 4:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b20f8a1a2081909081c36075d4ddbe |
completed | March 12, 2026, 12:57 a.m. |
| NEDg | Description generation | batch_69b2137b30508190a5a9a439d77ae3bb |
completed | March 12, 2026, 1:14 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b21413338c8190997d0f2f11f41008 |
completed | March 12, 2026, 1:17 a.m. |
Created at: March 8, 2026, 3:05 p.m.