Triple
T4088723
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuan Yin Temple (Honolulu) |
E87653
|
entity |
| Predicate | hasDeity |
P5606
|
FINISHED |
| Object | Guanyin |
E57606
|
NE FINISHED |
How this triple was built (2 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: Guanyin | Statement: [Kuan Yin Temple (Honolulu), hasDeity, Guanyin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Guanyin Context triple: [Kuan Yin Temple (Honolulu), hasDeity, Guanyin]
-
A.
Guanyin
chosen
Guanyin is a revered bodhisattva in East Asian Buddhism associated with compassion and mercy, often depicted as a protective and benevolent figure who hears the cries of the world.
-
B.
Amita
Amita is a skilled jeweler and member of the all-female heist crew in the film "Ocean's 8."
-
C.
Mazu
Mazu is a revered Chinese sea goddess and patron deity of sailors and coastal communities, especially venerated in southern China and Taiwan.
-
D.
Amida
Amida was the ancient name of the city now known as Diyarbakır, a historically significant fortified settlement in southeastern Anatolia.
-
E.
Benzaiten
Benzaiten is a Japanese Buddhist and Shinto goddess of music, eloquence, knowledge, and the arts, closely associated with water and often identified with the Hindu goddess Saraswati.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefca9e9088190a97cb2ccb5d622f0 |
completed | March 9, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b589d525fc8190be388452c220832e |
completed | March 14, 2026, 4:16 p.m. |
Created at: March 9, 2026, 3:39 p.m.