Triple
T13067970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ilocos Sur |
E329377
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Sta. Lucia
Sta. Lucia is a municipality in the province of Ilocos Sur in the Philippines, known for its agricultural economy and rural community character.
|
E1021732
|
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: Sta. Lucia | Statement: [Ilocos Sur, hasMunicipality, Sta. Lucia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sta. Lucia Context triple: [Ilocos Sur, hasMunicipality, Sta. Lucia]
-
A.
Maljamar
Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
-
B.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
-
C.
Currimao
Currimao is a coastal municipality in the Philippine province of Ilocos Norte known for its beaches, heritage sites, and fishing communities.
-
D.
Anahawan
Anahawan is a coastal municipality in the province of Southern Leyte in the Philippines, known for its rural communities and agricultural economy.
-
E.
Sto. Niño, Cagayan
Sto. Niño, Cagayan is a rural municipality in the province of Cagayan in the Philippines, known for its agricultural economy and small-town community character.
- 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: Sta. Lucia Triple: [Ilocos Sur, hasMunicipality, Sta. Lucia]
Generated description
Sta. Lucia is a municipality in the province of Ilocos Sur in the Philippines, known for its agricultural economy and rural community character.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sta. Lucia Target entity description: Sta. Lucia is a municipality in the province of Ilocos Sur in the Philippines, known for its agricultural economy and rural community character.
-
A.
Maljamar
Maljamar is a small unincorporated community in southeastern New Mexico known historically for its oil and gas activity.
-
B.
Marawila
Marawila is a coastal town in Sri Lanka known for its beaches, fishing community, and tourism-oriented resorts.
-
C.
Currimao
Currimao is a coastal municipality in the Philippine province of Ilocos Norte known for its beaches, heritage sites, and fishing communities.
-
D.
Anahawan
Anahawan is a coastal municipality in the province of Southern Leyte in the Philippines, known for its rural communities and agricultural economy.
-
E.
Sto. Niño, Cagayan
Sto. Niño, Cagayan is a rural municipality in the province of Cagayan in the Philippines, known for its agricultural economy and small-town community character.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ec8ba48190baf52c7823482680 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e26e5d6881908663444bca67b01e |
completed | May 3, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69f6e32bf5508190b4dc58971f8f64d0 |
completed | May 3, 2026, 5:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e40a13c8819084daf9b77b46a181 |
completed | May 3, 2026, 5:58 a.m. |
Created at: April 9, 2026, 9 p.m.