Triple
T18768811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalibo, Aklan |
E458959
|
entity |
| Predicate | hasBarangays |
P13208
|
FINISHED |
| Object |
Caano
Caano is a rural barangay within the municipality of Kalibo in the province of Aklan in the Philippines.
|
E1341471
|
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: Caano | Statement: [Kalibo, Aklan, hasBarangays, Caano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caano Context triple: [Kalibo, Aklan, hasBarangays, Caano]
-
A.
Joseph Calleia
Joseph Calleia was a Maltese-American character actor known for his distinctive voice and frequent roles as villains or tough figures in Hollywood films of the 1930s and 1940s.
-
B.
Molinaro
Molinaro is an Italian occupational surname, historically associated with millers and derived from the same root as "Molinero."
-
C.
Sciorra
Sciorra is the surname of Annabella Sciorra, an American actress known for her roles in films like "Jungle Fever" and the television series "The Sopranos."
-
D.
Fermani
Fermani are the inhabitants or natives of the Italian city of Fermo, located in the Marche region.
-
E.
Comano
Comano is a small municipality in Tuscany, Italy, known for its rural setting in the Apennine mountains and traditional local culture.
- 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: Caano Triple: [Kalibo, Aklan, hasBarangays, Caano]
Generated description
Caano is a rural barangay within the municipality of Kalibo in the province of Aklan in the Philippines.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Caano Target entity description: Caano is a rural barangay within the municipality of Kalibo in the province of Aklan in the Philippines.
-
A.
Joseph Calleia
Joseph Calleia was a Maltese-American character actor known for his distinctive voice and frequent roles as villains or tough figures in Hollywood films of the 1930s and 1940s.
-
B.
Molinaro
Molinaro is an Italian occupational surname, historically associated with millers and derived from the same root as "Molinero."
-
C.
Sciorra
Sciorra is the surname of Annabella Sciorra, an American actress known for her roles in films like "Jungle Fever" and the television series "The Sopranos."
-
D.
Fermani
Fermani are the inhabitants or natives of the Italian city of Fermo, located in the Marche region.
-
E.
Comano
Comano is a small municipality in Tuscany, Italy, known for its rural setting in the Apennine mountains and traditional local culture.
- 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_69d8d395dba0819087568404508590cb |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e58d867264819098ae35c9feab3bb4 |
completed | April 20, 2026, 2:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a053d450c8081908e44744a63e15fc3 |
completed | May 14, 2026, 3:11 a.m. |
| NEDg | Description generation | batch_6a053e7376ec8190950881d90d9fa567 |
completed | May 14, 2026, 3:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a053ef3600881908e39a4abe4e032e8 |
completed | May 14, 2026, 3:18 a.m. |
Created at: April 10, 2026, 11:52 a.m.