Triple
T12504743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cagayan |
E298919
|
entity |
| Predicate | hasCity |
P316
|
FINISHED |
| Object |
Camalaniugan
Camalaniugan is a municipality in the province of Cagayan in the Philippines, known for its historic churches and riverside setting along the Cagayan River.
|
E1008999
|
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: Camalaniugan | Statement: [Cagayan, hasCity, Camalaniugan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Camalaniugan Context triple: [Cagayan, hasCity, Camalaniugan]
-
A.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
-
B.
Miagao
Miagao is a coastal municipality in the Philippine province of Iloilo best known for its UNESCO-listed Miagao Church, a prime example of Baroque architecture.
-
C.
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.
-
D.
Maljamar
Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
-
E.
Anahawan
Anahawan is a coastal municipality in the province of Southern Leyte in the Philippines, known for its rural communities and agricultural economy.
- 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: Camalaniugan Triple: [Cagayan, hasCity, Camalaniugan]
Generated description
Camalaniugan is a municipality in the province of Cagayan in the Philippines, known for its historic churches and riverside setting along the Cagayan River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Camalaniugan Target entity description: Camalaniugan is a municipality in the province of Cagayan in the Philippines, known for its historic churches and riverside setting along the Cagayan River.
-
A.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
-
B.
Miagao
Miagao is a coastal municipality in the Philippine province of Iloilo best known for its UNESCO-listed Miagao Church, a prime example of Baroque architecture.
-
C.
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.
-
D.
Maljamar
Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
-
E.
Anahawan
Anahawan is a coastal municipality in the province of Southern Leyte in the Philippines, known for its rural communities and agricultural economy.
- 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_69f6a535943081909f893b2be006cc28 |
completed | May 3, 2026, 1:30 a.m. |
| NEDg | Description generation | batch_69f6a724e414819081c95b0d4ac0da25 |
completed | May 3, 2026, 1:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6a7def4bc8190836ad781a4a28456 |
completed | May 3, 2026, 1:41 a.m. |
Created at: April 8, 2026, 9:57 p.m.