Triple
T16122998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipality of Mariveles |
E391191
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
San Carlos
San Carlos is a barangay (village-level administrative division) within the municipality of Mariveles in the province of Bataan, Philippines.
|
E1196874
|
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 Carlos | Statement: [Municipality of Mariveles, hasBarangay, San Carlos]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Carlos Context triple: [Municipality of Mariveles, hasBarangay, San Carlos]
-
A.
San Carlos
San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
-
B.
San Carlos
San Carlos is a Nicaraguan town that serves as a key river and lake port near the southeastern end of Lake Nicaragua.
-
C.
San Carlos
San Carlos is a Chilean city known as an agricultural and commercial center in the Ñuble Region.
-
D.
San Carlos
San Carlos is a historic town in northwestern Argentina’s Salta Province, known for its colonial architecture, wine production, and role as a cultural hub in the Calchaquí Valleys.
-
E.
San Carlos
San Carlos is a municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
- 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 Carlos Triple: [Municipality of Mariveles, hasBarangay, San Carlos]
Generated description
San Carlos is a barangay (village-level administrative division) within the municipality of Mariveles in the province of Bataan, Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Carlos Target entity description: San Carlos is a barangay (village-level administrative division) within the municipality of Mariveles in the province of Bataan, Philippines.
-
A.
San Carlos
San Carlos is a municipality located in the Morazán Department of northeastern El Salvador, known for its rural character and mountainous surroundings.
-
B.
San Carlos
San Carlos is a city in San Mateo County, California, located on the San Francisco Peninsula between Belmont and Redwood City.
-
C.
San Carlos
San Carlos is a coastal component city in Negros Occidental, Philippines, known for its port, eco-tourism initiatives, and annual Pintaflores Festival.
-
D.
San Carlos
San Carlos is a Nicaraguan town that serves as a key river and lake port near the southeastern end of Lake Nicaragua.
-
E.
San Carlos
San Carlos is a Chilean city known as an agricultural and commercial center in the Ñuble Region.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e202027e78819091192aa62aedde13 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2a7fe308190a9a2ef7815e788c6 |
completed | May 10, 2026, 2:51 a.m. |
| NEDg | Description generation | batch_69fff3b25ba081909c396431ace865ac |
completed | May 10, 2026, 2:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff4a2964c8190bfa8c2fa0f934abe |
completed | May 10, 2026, 2:59 a.m. |
Created at: April 10, 2026, 5 a.m.