Triple
T3669417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Longshan Temple |
E77840
|
entity |
| Predicate | dedicatedTo |
P500
|
FINISHED |
| Object | Mazu |
E88708
|
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: Mazu | Statement: [Longshan Temple, dedicatedTo, Mazu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mazu Context triple: [Longshan Temple, dedicatedTo, Mazu]
-
A.
Mazu
chosen
Mazu is a revered Chinese sea goddess and patron deity of sailors and coastal communities, especially venerated in southern China and Taiwan.
-
B.
Chenghuangshen
Chenghuangshen is a traditional Chinese city god deity believed to protect and oversee the affairs, justice, and welfare of a specific city and its inhabitants.
-
C.
Guandi
Guandi is a revered Chinese deity, often identified with the historical general Guan Yu, who is worshipped as a god of war, loyalty, and righteousness in Chinese folk religion and beyond.
-
D.
Tōshō
Tōshō is the commonly used Japanese abbreviation for the Tokyo Stock Exchange, one of the world’s largest and most influential stock markets.
-
E.
Xuan Dieu
Xuan Dieu is a popular street and neighborhood in Hanoi’s Tay Ho District, known for its lakeside views, expatriate community, and vibrant mix of cafes, restaurants, and shops.
- 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_69ad85e083008190b2e1b7085fe500bd |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc42b3f94819091d51e488bc3f2f2 |
completed | March 8, 2026, 6:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b48850515c8190bdb9ddcfc0a13f4e |
completed | March 13, 2026, 9:57 p.m. |
Created at: March 8, 2026, 3:25 p.m.