Triple
T8079289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quezon |
E188573
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Atimonan
Atimonan is a coastal municipality in the province of Quezon in the Philippines, known for its fishing industry, scenic seaside views, and proximity to the Quezon Protected Landscape.
|
E710453
|
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: Atimonan | Statement: [Quezon, hasMunicipality, Atimonan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Atimonan Context triple: [Quezon, hasMunicipality, Atimonan]
-
A.
Tabogon
Tabogon is a coastal municipality in the province of Cebu in the Philippines, known for its agricultural lands and scenic seaside areas.
-
B.
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.
-
C.
Safotu
Safotu is a coastal village on the island of Savaiʻi in Samoa, known for its traditional Samoan culture and scenic beaches.
-
D.
Amadioha
Amadioha is a major deity in Igbo traditional religion, revered as the god of thunder, lightning, justice, and moral order.
-
E.
Ahangama
Ahangama is a coastal town in southern Sri Lanka known for its beaches, surfing spots, and traditional stilt fishermen.
- 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: Atimonan Triple: [Quezon, hasMunicipality, Atimonan]
Generated description
Atimonan is a coastal municipality in the province of Quezon in the Philippines, known for its fishing industry, scenic seaside views, and proximity to the Quezon Protected Landscape.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Atimonan Target entity description: Atimonan is a coastal municipality in the province of Quezon in the Philippines, known for its fishing industry, scenic seaside views, and proximity to the Quezon Protected Landscape.
-
A.
Tabogon
Tabogon is a coastal municipality in the province of Cebu in the Philippines, known for its agricultural lands and scenic seaside areas.
-
B.
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.
-
C.
Safotu
Safotu is a coastal village on the island of Savaiʻi in Samoa, known for its traditional Samoan culture and scenic beaches.
-
D.
Amadioha
Amadioha is a major deity in Igbo traditional religion, revered as the god of thunder, lightning, justice, and moral order.
-
E.
Ahangama
Ahangama is a coastal town in southern Sri Lanka known for its beaches, surfing spots, and traditional stilt fishermen.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a3f01c819096a2c9d5d5199fe6 |
completed | March 31, 2026, 3:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc63f79ac08190af49e77bee67921d |
completed | April 1, 2026, 12:16 a.m. |
| NEDg | Description generation | batch_69cc651d340c819089306bac7110f57a |
completed | April 1, 2026, 12:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc666ecc04819092ee4cc035dde627 |
completed | April 1, 2026, 12:27 a.m. |
Created at: March 30, 2026, 5:28 p.m.