Triple
T5964979
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siquijor Island |
E132728
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object |
Larena
Larena is a coastal municipality on Siquijor Island in the Philippines known historically as a key commercial and educational center of the province.
|
E559095
|
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: Larena | Statement: [Siquijor Island, hasMunicipality, Larena]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Larena Context triple: [Siquijor Island, hasMunicipality, Larena]
-
A.
Palena
Palena is a small town and municipality in the Palena Province of Chile’s Los Lagos Region, known for its remote Andean landscapes and outdoor tourism.
-
B.
Teroenza
Teroenza is a character in the Star Wars universe known for being one of the earlier owners of the iconic starship Millennium Falcon.
-
C.
Jandali
Jandali is an Arabic family name most notably associated with Abdulfattah Jandali, the biological father of Apple co-founder Steve Jobs.
-
D.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
E.
Nolano
Nolano is the Italian demonym for a person from the town of Nola in the Campania region of southern Italy.
- 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: Larena Triple: [Siquijor Island, hasMunicipality, Larena]
Generated description
Larena is a coastal municipality on Siquijor Island in the Philippines known historically as a key commercial and educational center of the province.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Larena Target entity description: Larena is a coastal municipality on Siquijor Island in the Philippines known historically as a key commercial and educational center of the province.
-
A.
Palena
Palena is a small town and municipality in the Palena Province of Chile’s Los Lagos Region, known for its remote Andean landscapes and outdoor tourism.
-
B.
Teroenza
Teroenza is a character in the Star Wars universe known for being one of the earlier owners of the iconic starship Millennium Falcon.
-
C.
Jandali
Jandali is an Arabic family name most notably associated with Abdulfattah Jandali, the biological father of Apple co-founder Steve Jobs.
-
D.
Laja
Laja is a small Chilean city in the Biobío Region, known for its riverside setting and proximity to the Biobío River.
-
E.
Nolano
Nolano is the Italian demonym for a person from the town of Nola in the Campania region of southern Italy.
- 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_69c0086c2364819091e9fe2f58fa2517 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03a3ca1dc819098cde8ae5ec1d845 |
completed | March 22, 2026, 6:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0e3f32e8481908a6075684287c412 |
completed | March 23, 2026, 6:55 a.m. |
| NEDg | Description generation | batch_69c0ebfa3a9c81908a183f995350366b |
completed | March 23, 2026, 7:30 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0ec61672c8190b98cead75cac84d5 |
completed | March 23, 2026, 7:31 a.m. |
Created at: March 22, 2026, 4:03 p.m.