Triple
T28158533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lishui River |
E714822
|
entity |
| Predicate | hasScenicArea |
P29946
|
FINISHED |
| Object |
Zhangjiajie karst landscape
The Zhangjiajie karst landscape is a renowned scenic area in China famous for its towering sandstone pillars, deep ravines, and mist-shrouded peaks that inspired the floating mountains in the film "Avatar."
|
E1826881
|
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: Zhangjiajie karst landscape | Statement: [Lishui River, hasScenicArea, Zhangjiajie karst landscape]
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: Zhangjiajie karst landscape Triple: [Lishui River, hasScenicArea, Zhangjiajie karst landscape]
Generated description
The Zhangjiajie karst landscape is a renowned scenic area in China famous for its towering sandstone pillars, deep ravines, and mist-shrouded peaks that inspired the floating mountains in the film "Avatar."
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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f641e9eac08190976874fc569b4a63 |
completed | May 2, 2026, 6:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1cc358df5c819099e15c1b4b2041d2 |
completed | May 31, 2026, 11:25 p.m. |
| NEDg | Description generation | batch_6a1cc3c360808190a2961b3e0a3c839f |
completed | May 31, 2026, 11:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1cc45223488190a914244c6245a86f |
completed | May 31, 2026, 11:29 p.m. |
Created at: April 27, 2026, 10:04 p.m.