Triple
T3898781
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zambales |
E90435
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
San Antonio
San Antonio is a coastal municipality in the Philippine province of Zambales known for its beaches, coves, and nearby island-hopping destinations.
|
E445160
|
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: San Antonio | Statement: [Zambales, hasMunicipality, San Antonio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Antonio Context triple: [Zambales, hasMunicipality, San Antonio]
-
A.
San Antonio
San Antonio was one of the ships in Ferdinand Magellan’s expedition fleet that participated in the first circumnavigation attempt of the globe.
-
B.
San Antonio
San Antonio is a barangay in the municipality of Los Baños in the province of Laguna, Philippines.
-
C.
San Antonio
San Antonio is a large, historic city in south-central Texas known for the Alamo, the River Walk, and its rich blend of Mexican and Texan culture.
-
D.
San Antonio
San Antonio is a major Chilean port city known for its significant role in the country’s maritime trade and fishing industries.
-
E.
San Antonio
San Antonio is a coastal municipality in the province of Northern Samar in the Philippines, known for its island beaches and fishing communities.
- 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: San Antonio Triple: [Zambales, hasMunicipality, San Antonio]
Generated description
San Antonio is a coastal municipality in the Philippine province of Zambales known for its beaches, coves, and nearby island-hopping destinations.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Antonio Target entity description: San Antonio is a coastal municipality in the Philippine province of Zambales known for its beaches, coves, and nearby island-hopping destinations.
-
A.
San Antonio
San Antonio is a large, historic city in south-central Texas known for the Alamo, the River Walk, and its rich blend of Mexican and Texan culture.
-
B.
San Antonio
San Antonio was one of the ships in Ferdinand Magellan’s expedition fleet that participated in the first circumnavigation attempt of the globe.
-
C.
San Antonio
San Antonio is a major Chilean port city known for its significant role in the country’s maritime trade and fishing industries.
-
D.
San Antonio
San Antonio is a barangay in the municipality of Los Baños in the province of Laguna, Philippines.
-
E.
San Antonio
San Antonio is a coastal municipality in the province of Northern Samar in the Philippines, known for its island beaches and fishing communities.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeecefa3608190a7a20ed6df6a64b2 |
completed | March 9, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b67b9e1b4081909f53466a603d7061 |
completed | March 15, 2026, 9:27 a.m. |
| NEDg | Description generation | batch_69b67c5de2dc819095642ed99a9b9ec6 |
completed | March 15, 2026, 9:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b67d1d3f9081909541b3a2bab7d0e7 |
completed | March 15, 2026, 9:34 a.m. |
Created at: March 9, 2026, 3:21 p.m.