Triple
T8798909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dragon King |
E209351
|
entity |
| Predicate | script |
P505
|
FINISHED |
| Object | 龍王 |
E209351
|
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: 龍王 | Statement: [Dragon King, script, 龍王]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: 龍王 Context triple: [Dragon King, script, 龍王]
-
A.
Crouching Dragon
Crouching Dragon is the famous style name of Zhuge Liang, the legendary strategist and statesman of the Three Kingdoms period in Chinese history.
-
B.
Nine Dragons
"Nine Dragons" is a crime novel by Michael Connelly featuring LAPD detective Harry Bosch as he investigates a case that takes him from Los Angeles to Hong Kong.
-
C.
Dragon King
chosen
The Dragon King is a prominent water and weather deity in Chinese tradition, revered as the ruler of seas, rivers, and rainfall.
-
D.
Dragon King
The Dragon King is the official title of the reigning monarch of Bhutan, symbolizing the country's spiritual and cultural identity.
-
E.
The Dragon
The Dragon is the legendary Chinese table tennis player Ma Long, widely regarded as one of the greatest and most dominant players in the sport’s history.
- 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fb7491c8190bcdb98d6cc003d9e |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6f658f248190957eba821b07cc4f |
completed | April 3, 2026, 7:42 a.m. |
Created at: March 30, 2026, 6:44 p.m.