Triple
T35670524
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 石景山区 |
E1030702
|
entity |
| Predicate | hasAttraction |
P105
|
FINISHED |
| Object |
模式口历史文化街区
模式口历史文化街区是位于北京市石景山区的一处以明清古街风貌和传统民居建筑保存完好而闻名的历史文化街区。
|
E2151594
|
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: 模式口历史文化街区 | Statement: [石景山区, hasAttraction, 模式口历史文化街区]
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: 模式口历史文化街区 Triple: [石景山区, hasAttraction, 模式口历史文化街区]
Generated description
模式口历史文化街区是位于北京市石景山区的一处以明清古街风貌和传统民居建筑保存完好而闻名的历史文化街区。
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_69f76e0acfc0819082c8495c2210ce73 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f79fb2069881908fe6b19f28d2fb81 |
completed | May 3, 2026, 7:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a387283403481909b75d52cd32abc29 |
completed | June 21, 2026, 11:23 p.m. |
| NEDg | Description generation | batch_6a387348579c81909fd91162bbf8792c |
completed | June 21, 2026, 11:27 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a38744e5a9c81909b7a8ce5f27c8eb8 |
completed | June 21, 2026, 11:31 p.m. |
Created at: May 3, 2026, 4:05 p.m.