Triple
T3152325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eastern Samar |
E65903
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
San Julian
San Julian is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
|
E330843
|
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 Julian | Statement: [Eastern Samar, hasMunicipality, San Julian]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Julian Context triple: [Eastern Samar, hasMunicipality, San Julian]
-
A.
San Martin
San Martin is a small unincorporated community in Santa Clara County, California, located in the southern Santa Clara Valley between Morgan Hill and Gilroy.
-
B.
Carabajal
Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
-
C.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
D.
Herrero
Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
-
E.
San Juan y Martínez
San Juan y Martínez is a Cuban town and municipality in the western province of Pinar del Río, known especially for its tobacco cultivation.
- 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 Julian Triple: [Eastern Samar, hasMunicipality, San Julian]
Generated description
San Julian is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Julian Target entity description: San Julian is a coastal municipality in the province of Eastern Samar in the Philippines, known for its rural communities and Pacific shoreline.
-
A.
San Martin
San Martin is a small unincorporated community in Santa Clara County, California, located in the southern Santa Clara Valley between Morgan Hill and Gilroy.
-
B.
Carabajal
Carabajal is a Spanish-origin surname, often considered a variant of Carvajal, borne by various families across Spain and Latin America.
-
C.
Montalva
Montalva is a Spanish-language surname notably associated with Chilean president Eduardo Frei Montalva.
-
D.
Herrero
Herrero is a Spanish occupational surname derived from the word for "blacksmith" or "smith."
-
E.
San Juan y Martínez
San Juan y Martínez is a Cuban town and municipality in the western province of Pinar del Río, known especially for its tobacco cultivation.
- 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_69ad8584485081909ed529e890cadc4a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada5c27258819099c46a657779780b |
completed | March 8, 2026, 4:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2250088c48190a226031afda38d87 |
completed | March 12, 2026, 2:29 a.m. |
| NEDg | Description generation | batch_69b2258a16a8819080f4bac7a63fa145 |
completed | March 12, 2026, 2:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b225e072908190bcdde199b1ec2f4c |
completed | March 12, 2026, 2:33 a.m. |
Created at: March 8, 2026, 3:05 p.m.