Triple
T11673653
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gateless Gate |
E277438
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object |
Wumenguan
Wumenguan is a classic 13th-century Chinese Zen (Chan) Buddhist koan collection compiled by the monk Wumen Huikai, widely studied in Zen practice.
|
E940296
|
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: Wumenguan | Statement: [Gateless Gate, hasTitle, Wumenguan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wumenguan Context triple: [Gateless Gate, hasTitle, Wumenguan]
-
A.
Wutong Mountain
Wutong Mountain is a prominent scenic peak in Shenzhen, China, known for its hiking trails, lush forests, and panoramic views over the city and coastline.
-
B.
Tuizhi
Tuizhi is the courtesy name of Han Yu, a prominent Tang dynasty Confucian scholar, essayist, and poet known for advocating classical prose.
-
C.
Hehuanshan
Hehuanshan is a high-altitude mountain and popular scenic area in Taiwan, known for its alpine landscapes, hiking trails, and seasonal snow.
-
D.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
-
E.
Pizhou
Pizhou is a county-level city administered by Xuzhou in Jiangsu Province, eastern China, known for its historical sites and regional commerce.
- 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: Wumenguan Triple: [Gateless Gate, hasTitle, Wumenguan]
Generated description
Wumenguan is a classic 13th-century Chinese Zen (Chan) Buddhist koan collection compiled by the monk Wumen Huikai, widely studied in Zen practice.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Wumenguan Target entity description: Wumenguan is a classic 13th-century Chinese Zen (Chan) Buddhist koan collection compiled by the monk Wumen Huikai, widely studied in Zen practice.
-
A.
Wutong Mountain
Wutong Mountain is a prominent scenic peak in Shenzhen, China, known for its hiking trails, lush forests, and panoramic views over the city and coastline.
-
B.
Tuizhi
Tuizhi is the courtesy name of Han Yu, a prominent Tang dynasty Confucian scholar, essayist, and poet known for advocating classical prose.
-
C.
Hehuanshan
Hehuanshan is a high-altitude mountain and popular scenic area in Taiwan, known for its alpine landscapes, hiking trails, and seasonal snow.
-
D.
Daliang
Daliang was the principal city and political center of the ancient Chinese State of Wei during the Warring States period.
-
E.
Pizhou
Pizhou is a county-level city administered by Xuzhou in Jiangsu Province, eastern China, known for its historical sites and regional commerce.
- 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_69d6aafd0a448190b44da30af8c6c519 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a443b6848190a1eb6825fbc49d08 |
completed | April 10, 2026, 7:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef13e1b3d8819085ea806280ed69d3 |
completed | April 27, 2026, 7:44 a.m. |
| NEDg | Description generation | batch_69ef3551b9a88190a9b30bcb2592628b |
completed | April 27, 2026, 10:07 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef51c17078819083f05036f290ce09 |
completed | April 27, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:40 p.m.