Triple
T14503587
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pangasinan |
E340205
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Sta. Barbara
Sta. Barbara is a landlocked municipality in the province of Pangasinan in the Philippines, known for its agricultural economy and growing suburban communities.
|
E1103009
|
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. Barbara | Statement: [Pangasinan, hasMunicipality, Sta. Barbara]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sta. Barbara Context triple: [Pangasinan, hasMunicipality, Sta. Barbara]
-
A.
Sta. Maria
Sta. Maria is a coastal municipality in the Philippine province of Ilocos Sur known for its historic church and agricultural communities.
-
B.
Sta. Maria
Sta. Maria is a coastal municipality in the province of Davao Occidental in the southern Philippines, known for its agricultural and fishing-based local economy.
-
C.
Sta. Elena
Sta. Elena is a rural municipality in the Philippine province of Camarines Norte known for its agricultural communities and small-town character.
-
D.
Santa Bárbara
Santa Bárbara is a civil parish within the municipality of Ponta Delgada in the Azores, Portugal.
-
E.
Santa Bárbara
Santa Bárbara is a locality within the Mexican state of Nueva Vizcaya, historically part of New Spain in the colonial era.
- 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. Barbara Triple: [Pangasinan, hasMunicipality, Sta. Barbara]
Generated description
Sta. Barbara is a landlocked municipality in the province of Pangasinan in the Philippines, known for its agricultural economy and growing suburban communities.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sta. Barbara Target entity description: Sta. Barbara is a landlocked municipality in the province of Pangasinan in the Philippines, known for its agricultural economy and growing suburban communities.
-
A.
Sta. Maria
Sta. Maria is a coastal municipality in the Philippine province of Ilocos Sur known for its historic church and agricultural communities.
-
B.
Sta. Maria
Sta. Maria is a coastal municipality in the province of Davao Occidental in the southern Philippines, known for its agricultural and fishing-based local economy.
-
C.
Sta. Elena
Sta. Elena is a rural municipality in the Philippine province of Camarines Norte known for its agricultural communities and small-town character.
-
D.
Santa Bárbara
Santa Bárbara is a locality within the Mexican state of Nueva Vizcaya, historically part of New Spain in the colonial era.
-
E.
Santa Bárbara
Santa Bárbara is a civil parish within the municipality of Ponta Delgada in the Azores, Portugal.
- 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_69d822d9c0408190b9a2b3643e58bb4d |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69de94e0f9048190a2d266cfa4f9dfb6 |
completed | April 14, 2026, 7:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d9dba1081909154362b922a2417 |
completed | May 8, 2026, 4:59 a.m. |
| NEDg | Description generation | batch_69fd6f24431c81908a25ad81c28da56d |
completed | May 8, 2026, 5:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd6ff5a58881909987fa653e58a197 |
completed | May 8, 2026, 5:09 a.m. |
Created at: April 10, 2026, 1:21 a.m.