Triple
T6082984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Balinese people |
E135567
|
entity |
| Predicate | traditionalDance |
P1114
|
FINISHED |
| Object |
Pendet
Pendet is a traditional Balinese dance, originally a temple offering dance, that welcomes deities and guests with graceful, ritualized movements.
|
E566682
|
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: Pendet | Statement: [Balinese people, traditionalDance, Pendet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pendet Context triple: [Balinese people, traditionalDance, Pendet]
-
A.
Penge
Penge is a suburban district in southeast London known for its Victorian architecture and proximity to Crystal Palace.
-
B.
Pitadeniya
Pitadeniya is a village and gateway area in southern Sri Lanka that serves as a main entry point for visitors to the Sinharaja Forest Reserve.
-
C.
Pemuteran
Pemuteran is a coastal village in northwest Bali, Indonesia, known for its tranquil beaches, coral reef restoration projects, and relaxed, less-touristed atmosphere.
-
D.
Persenet
Persenet was an ancient Egyptian queen of the 4th Dynasty, known primarily as a consort of Pharaoh Menkaure.
-
E.
Peng
Peng is a Chinese surname borne by numerous notable figures in politics, arts, and academia throughout Chinese history and the modern era.
- 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: Pendet Triple: [Balinese people, traditionalDance, Pendet]
Generated description
Pendet is a traditional Balinese dance, originally a temple offering dance, that welcomes deities and guests with graceful, ritualized movements.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pendet Target entity description: Pendet is a traditional Balinese dance, originally a temple offering dance, that welcomes deities and guests with graceful, ritualized movements.
-
A.
Penge
Penge is a suburban district in southeast London known for its Victorian architecture and proximity to Crystal Palace.
-
B.
Pitadeniya
Pitadeniya is a village and gateway area in southern Sri Lanka that serves as a main entry point for visitors to the Sinharaja Forest Reserve.
-
C.
Pemuteran
Pemuteran is a coastal village in northwest Bali, Indonesia, known for its tranquil beaches, coral reef restoration projects, and relaxed, less-touristed atmosphere.
-
D.
Persenet
Persenet was an ancient Egyptian queen of the 4th Dynasty, known primarily as a consort of Pharaoh Menkaure.
-
E.
Peng
Peng is a Chinese surname borne by numerous notable figures in politics, arts, and academia throughout Chinese history and the modern era.
- 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_69c0087ad31c8190ab936e0ff28614b6 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05786233c81909010a6c2f7e7dfda |
completed | March 22, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c11d57b5f481908d7df374837a486a |
completed | March 23, 2026, 11 a.m. |
| NEDg | Description generation | batch_69c11e89c75481908381df126a7b1661 |
completed | March 23, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c11ef6971c8190b8dde5568b330b41 |
completed | March 23, 2026, 11:07 a.m. |
Created at: March 22, 2026, 4:11 p.m.