Triple
T3152313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Samar |
E65903
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Oras
Oras is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
|
E330973
|
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: Oras | Statement: [Eastern Samar, hasMunicipality, Oras]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Oras Context triple: [Eastern Samar, hasMunicipality, Oras]
-
A.
Stolica
Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
-
B.
Orani
Orani is a coastal municipality in the province of Bataan in the Philippines, known for its fishing industry, agricultural lands, and proximity to Manila Bay.
-
C.
Thaton
Thaton is an ancient city in southern Myanmar historically significant as a major center of the Mon kingdom and Theravada Buddhism in the region.
-
D.
Cité
Cité is a Paris Métro station located on the Île de la Cité in the historic center of Paris.
-
E.
Metropolia
Metropolia was the former name of the Russian Orthodox Greek Catholic Church of America, the predecessor body that evolved into today’s Orthodox Church in America.
- 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: Oras Triple: [Eastern Samar, hasMunicipality, Oras]
Generated description
Oras is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Oras Target entity description: Oras is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
-
A.
Stolica
Stolica is the highest peak of the Slovak Ore Mountains in central Slovakia, known for its forested slopes and scenic hiking routes.
-
B.
Orani
Orani is a coastal municipality in the province of Bataan in the Philippines, known for its fishing industry, agricultural lands, and proximity to Manila Bay.
-
C.
Thaton
Thaton is an ancient city in southern Myanmar historically significant as a major center of the Mon kingdom and Theravada Buddhism in the region.
-
D.
Cité
Cité is a Paris Métro station located on the Île de la Cité in the historic center of Paris.
-
E.
Metropolia
Metropolia was the former name of the Russian Orthodox Greek Catholic Church of America, the predecessor body that evolved into today’s Orthodox Church in America.
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5c27258819099c46a657779780b |
completed | March 8, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2250088c48190a226031afda38d87 |
completed | March 12, 2026, 2:29 a.m. |
| NEDg | Description generation | batch_69b225896c4c81909e875a2d357e7bc5 |
completed | March 12, 2026, 2:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b226000fe88190b73f34e73e85ff48 |
completed | March 12, 2026, 2:33 a.m. |
Created at: March 8, 2026, 3:05 p.m.