Triple
T28423879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Emperor Ping of Han |
E720018
|
entity |
| Predicate | burialPlace |
P196
|
FINISHED |
| Object |
Pingling Mausoleum
Pingling Mausoleum is the imperial tomb complex of Emperor Ping of the Western Han dynasty, located near modern Xi'an in Shaanxi, China.
|
E1831140
|
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: Pingling Mausoleum | Statement: [Emperor Ping of Han, burialPlace, Pingling Mausoleum]
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: Pingling Mausoleum Triple: [Emperor Ping of Han, burialPlace, Pingling Mausoleum]
Generated description
Pingling Mausoleum is the imperial tomb complex of Emperor Ping of the Western Han dynasty, located near modern Xi'an in Shaanxi, China.
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_69eff6f1c5088190bc24bfbf92f9c017 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64dfc22188190a71aa737d6320d61 |
completed | May 2, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1ccf23ca8c8190b6e061e04a414d80 |
completed | June 1, 2026, 12:15 a.m. |
| NEDg | Description generation | batch_6a1ccff86fc88190b1438e77f3a5f101 |
completed | June 1, 2026, 12:19 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a24946ccd908190ae144fbc7010aca9 |
completed | June 6, 2026, 9:43 p.m. |
Created at: April 28, 2026, 1:35 a.m.