Triple
T29084975
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingdom of Patan |
E734082
|
entity |
| Predicate | hasSite |
P1205
|
FINISHED |
| Object |
Golden Temple of Patan
The Golden Temple of Patan is a historic Newar Buddhist monastery in Lalitpur, Nepal, renowned for its richly gilded façade, intricate metalwork, and central role in local religious life.
|
E1846585
|
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: Golden Temple of Patan | Statement: [Kingdom of Patan, hasSite, Golden Temple of Patan]
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: Golden Temple of Patan Triple: [Kingdom of Patan, hasSite, Golden Temple of Patan]
Generated description
The Golden Temple of Patan is a historic Newar Buddhist monastery in Lalitpur, Nepal, renowned for its richly gilded façade, intricate metalwork, and central role in local religious life.
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_69f05b0c0f28819086eae6e84f2ae472 |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f6614638d481909dd167f9c8c7055c |
completed | May 2, 2026, 8:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a251f8f9fdc8190bc24dbcfedb7ddcc |
completed | June 7, 2026, 7:36 a.m. |
| NEDg | Description generation | batch_6a2523eced288190ba098d552a92ea6d |
completed | June 7, 2026, 7:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a2524951aa88190868ecdfccc99862b |
completed | June 7, 2026, 7:58 a.m. |
Created at: April 28, 2026, 10:59 a.m.