Triple
T36837309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leo le Gris |
E910307
|
entity |
| Predicate | belongsToTradition |
P6900
|
FINISHED |
| Object |
Hispanic poetry
Hispanic poetry is a rich literary tradition encompassing verse written in Spanish (and related Iberian and Latin American languages), known for its diverse historical periods, regional voices, and themes of identity, love, politics, and spirituality.
|
E1761425
|
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: Hispanic poetry | Statement: [Leo le Gris, belongsToTradition, Hispanic poetry]
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: Hispanic poetry Triple: [Leo le Gris, belongsToTradition, Hispanic poetry]
Generated description
Hispanic poetry is a rich literary tradition encompassing verse written in Spanish (and related Iberian and Latin American languages), known for its diverse historical periods, regional voices, and themes of identity, love, politics, and spirituality.
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_69f76e7e9d60819092442fba73290a46 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7cf7f28348190bdf38395e66f7033 |
completed | May 3, 2026, 10:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3dde722de8819088707a69406c30c9 |
completed | June 26, 2026, 2:05 a.m. |
| NEDg | Description generation | batch_6a3de007551c8190987f689f90968eed |
completed | June 26, 2026, 2:12 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3de48f5cc48190b6ede4caf8298853 |
completed | June 26, 2026, 2:31 a.m. |
Created at: May 3, 2026, 4:13 p.m.