Triple
T26449993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bortala River |
E665320
|
entity |
| Predicate | watercourseThrough |
P165
|
FINISHED |
| Object |
Bole City
Bole City is a county-level city in Xinjiang, China, known as the administrative seat of Bortala Mongol Autonomous Prefecture and a regional hub near the border with Kazakhstan.
|
E1723724
|
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: Bole City | Statement: [Bortala River, watercourseThrough, Bole City]
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: Bole City Triple: [Bortala River, watercourseThrough, Bole City]
Generated description
Bole City is a county-level city in Xinjiang, China, known as the administrative seat of Bortala Mongol Autonomous Prefecture and a regional hub near the border with Kazakhstan.
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_69ee883d5040819097dd154643005230 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f612641a10819083c65b529fdade2a |
completed | May 2, 2026, 3:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a11aed569ac81908bfb73dc5df4cd5c |
completed | May 23, 2026, 1:42 p.m. |
| NEDg | Description generation | batch_6a11af6832f08190ab2673c8502f0526 |
completed | May 23, 2026, 1:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a11b0097edc81909327051db358c7b1 |
completed | May 23, 2026, 1:47 p.m. |
Created at: April 27, 2026, 12:04 a.m.