Triple
T11062143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badian |
E261532
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object |
Zaragosa
Zaragosa is a barangay (village-level administrative division) within the municipality of Badian in the province of Cebu, Philippines.
|
E908302
|
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: Zaragosa | Statement: [Badian, hasBarangay, Zaragosa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zaragosa Context triple: [Badian, hasBarangay, Zaragosa]
-
A.
Zaragoza
Zaragoza is a metro station on Mexico City’s Line 1 that serves as a key eastern access point to the city’s rapid transit network.
-
B.
Zaragoza
Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
-
C.
Zaragoza
Zaragoza is a small municipality and town in the northern Mexican state of Coahuila, known for its rural character and proximity to the U.S. border.
-
D.
Burgos
Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
-
E.
Burgos
Burgos is a small coastal municipality on the northern tip of Siargao Island in the Philippines, known for its quiet beaches and surf spots.
- 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: Zaragosa Triple: [Badian, hasBarangay, Zaragosa]
Generated description
Zaragosa is a barangay (village-level administrative division) within the municipality of Badian in the province of Cebu, Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zaragosa Target entity description: Zaragosa is a barangay (village-level administrative division) within the municipality of Badian in the province of Cebu, Philippines.
-
A.
Zaragoza
Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
-
B.
Zaragoza
Zaragoza is a metro station on Mexico City’s Line 1 that serves as a key eastern access point to the city’s rapid transit network.
-
C.
Zaragoza
Zaragoza is a small municipality and town in the northern Mexican state of Coahuila, known for its rural character and proximity to the U.S. border.
-
D.
Burgos
Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
-
E.
Burgos
Burgos is a small coastal municipality on the northern tip of Siargao Island in the Philippines, known for its quiet beaches and surf spots.
- 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_69d6aa98650481908609c7c56bfa7902 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d798eb838c819089a89c55209c0295 |
completed | April 9, 2026, 12:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e462d34c0081908067d91c163c118c |
completed | April 19, 2026, 5:06 a.m. |
| NEDg | Description generation | batch_69e46c3448348190b2c062d21771066d |
completed | April 19, 2026, 5:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e46dadbc5c8190b41279a05731dc95 |
completed | April 19, 2026, 5:52 a.m. |
Created at: April 8, 2026, 9:26 p.m.