Triple
T12504750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cagayan |
E298919
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Baggao
Baggao is a municipality in the province of Cagayan in the Philippines, known for its rural landscapes and agricultural economy.
|
E986706
|
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: Baggao | Statement: [Cagayan, hasCity, Baggao]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Baggao Context triple: [Cagayan, hasCity, Baggao]
-
A.
Mount Binaiya
Mount Binaiya is the highest mountain on the Indonesian island of Seram, known for its rugged terrain and rich biodiversity.
-
B.
Mount Samat
Mount Samat is a historic mountain in Bataan, Philippines, known as a World War II memorial site commemorating the Battle of Bataan.
-
C.
Mount Banahaw
Mount Banahaw is an active, sacred stratovolcano in the Philippines revered by pilgrims and mystics and known for its rich biodiversity and hiking trails.
-
D.
Himamaylan
Himamaylan is a coastal component city in the southern part of Negros Occidental in the Philippines, known historically as one of the province’s older settlements.
-
E.
Mount Guiting-Guiting
Mount Guiting-Guiting is a rugged, pyramid-shaped mountain in the Philippines renowned among hikers and climbers for its challenging trails and rich biodiversity.
- 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: Baggao Triple: [Cagayan, hasCity, Baggao]
Generated description
Baggao is a municipality in the province of Cagayan in the Philippines, known for its rural landscapes and agricultural economy.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Baggao Target entity description: Baggao is a municipality in the province of Cagayan in the Philippines, known for its rural landscapes and agricultural economy.
-
A.
Mount Binaiya
Mount Binaiya is the highest mountain on the Indonesian island of Seram, known for its rugged terrain and rich biodiversity.
-
B.
Mount Samat
Mount Samat is a historic mountain in Bataan, Philippines, known as a World War II memorial site commemorating the Battle of Bataan.
-
C.
Mount Banahaw
Mount Banahaw is an active, sacred stratovolcano in the Philippines revered by pilgrims and mystics and known for its rich biodiversity and hiking trails.
-
D.
Himamaylan
Himamaylan is a coastal component city in the southern part of Negros Occidental in the Philippines, known historically as one of the province’s older settlements.
-
E.
Mount Guiting-Guiting
Mount Guiting-Guiting is a rugged, pyramid-shaped mountain in the Philippines renowned among hikers and climbers for its challenging trails and rich biodiversity.
- 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_69d6ada4cd388190ae3bbf83ff87057a |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94dfddf38819099263b8b1e804736 |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bb5af708190b3786da334c3bf23 |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce1b0ec8190bcbd245255e548b5 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64da735f48190b051ce173c13e5b2 |
completed | May 2, 2026, 7:16 p.m. |
Created at: April 8, 2026, 9:57 p.m.