Triple
T16396926
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Narciso, Zambales |
E398206
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
San Pascual
San Pascual is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
|
E1209596
|
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 Pascual | Statement: [San Narciso, Zambales, hasBarangay, San Pascual]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Pascual Context triple: [San Narciso, Zambales, hasBarangay, San Pascual]
-
A.
San Pascual
San Pascual is a coastal municipality in the province of Batangas in the Philippines, known for its mix of residential communities and industrial facilities.
-
B.
San Pascual
San Pascual is a coastal municipality in the Philippine province of Masbate known for its island landscapes and fishing-based local economy.
-
C.
San Pedro Ayampuc
San Pedro Ayampuc is a municipality and town located near Guatemala City in the Guatemala Department of Guatemala.
-
D.
San Cosme
San Cosme is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near the historic center of the city.
-
E.
Cuencamé
Cuencamé is a municipality and town in the Mexican state of Durango, historically part of the colonial province of Nueva Vizcaya.
- 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 Pascual Triple: [San Narciso, Zambales, hasBarangay, San Pascual]
Generated description
San Pascual is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Pascual Target entity description: San Pascual is a barangay (village-level administrative division) within the municipality of San Narciso in the province of Zambales, Philippines.
-
A.
San Pascual
San Pascual is a coastal municipality in the province of Batangas in the Philippines, known for its mix of residential communities and industrial facilities.
-
B.
San Pascual
San Pascual is a coastal municipality in the Philippine province of Masbate known for its island landscapes and fishing-based local economy.
-
C.
San Pedro Ayampuc
San Pedro Ayampuc is a municipality and town located near Guatemala City in the Guatemala Department of Guatemala.
-
D.
San Cosme
San Cosme is a Mexico City Metro station on Line 2 that serves the San Rafael neighborhood near the historic center of the city.
-
E.
Cuencamé
Cuencamé is a municipality and town in the Mexican state of Durango, historically part of the colonial province of Nueva Vizcaya.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e327cb3c708190b64341cb1410ed81 |
completed | April 18, 2026, 6:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00357838a88190be88c51f454be6eb |
completed | May 10, 2026, 7:36 a.m. |
| NEDg | Description generation | batch_6a0035ea77dc8190bda37dac2710d0e3 |
completed | May 10, 2026, 7:38 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0036e53f2c81908f04a5e51870040c |
completed | May 10, 2026, 7:42 a.m. |
Created at: April 10, 2026, 5:09 a.m.