Triple
T18003056
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magayon |
E430674
|
entity |
| Predicate | hasLover |
P9994
|
FINISHED |
| Object |
Panganoron
Panganoron is a figure in Philippine Bicolano legend known as the lover of the maiden Magayon in the tragic love story associated with Mount Mayon.
|
E1300290
|
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: Panganoron | Statement: [Magayon, hasLover, Panganoron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Panganoron Context triple: [Magayon, hasLover, Panganoron]
-
A.
Menua
Menua was a prominent king of the ancient kingdom of Urartu, known for expanding its territory and developing extensive irrigation and fortification projects.
-
B.
Arzo
Arzo is a village and former municipality in the canton of Ticino in southern Switzerland, now part of the municipality of Mendrisio.
-
C.
Pakoštane
Pakoštane is a coastal village and popular tourist destination in Croatia, situated between the Adriatic Sea and Lake Vrana.
-
D.
Tepti-ahar
Tepti-ahar was a king of the Middle Elamite period in ancient Elam, known from inscriptions that attest to his rule in southwestern Iran.
-
E.
Pandesara
Pandesara is an industrial and residential suburb located within the Surat metropolitan region in the Indian state of Gujarat.
- 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: Panganoron Triple: [Magayon, hasLover, Panganoron]
Generated description
Panganoron is a figure in Philippine Bicolano legend known as the lover of the maiden Magayon in the tragic love story associated with Mount Mayon.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Panganoron Target entity description: Panganoron is a figure in Philippine Bicolano legend known as the lover of the maiden Magayon in the tragic love story associated with Mount Mayon.
-
A.
Menua
Menua was a prominent king of the ancient kingdom of Urartu, known for expanding its territory and developing extensive irrigation and fortification projects.
-
B.
Arzo
Arzo is a village and former municipality in the canton of Ticino in southern Switzerland, now part of the municipality of Mendrisio.
-
C.
Pakoštane
Pakoštane is a coastal village and popular tourist destination in Croatia, situated between the Adriatic Sea and Lake Vrana.
-
D.
Tepti-ahar
Tepti-ahar was a king of the Middle Elamite period in ancient Elam, known from inscriptions that attest to his rule in southwestern Iran.
-
E.
Pandesara
Pandesara is an industrial and residential suburb located within the Surat metropolitan region in the Indian state of Gujarat.
- 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_69d8b904530081908bf341d842464856 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4b3ea60608190b977644e946407b7 |
completed | April 19, 2026, 10:52 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0337b6b7e48190a649dda888450b2d |
completed | May 12, 2026, 2:22 p.m. |
| NEDg | Description generation | batch_6a033ca755e08190aa5003164b49f196 |
completed | May 12, 2026, 2:43 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a033d7a601c8190a4746adfdfffbca8 |
completed | May 12, 2026, 2:47 p.m. |
Created at: April 10, 2026, 10:23 a.m.