Triple
T35708678
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suite persane |
E1031790
|
entity |
| Predicate | movement |
P81
|
FINISHED |
| Object |
III. Marche persane
III. Marche persane is the lively, march-style third movement of the orchestral Suite persane by French composer André Caplet, evoking an exoticized Persian atmosphere.
|
E2152584
|
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: III. Marche persane | Statement: [Suite persane, movement, III. Marche persane]
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: III. Marche persane Triple: [Suite persane, movement, III. Marche persane]
Generated description
III. Marche persane is the lively, march-style third movement of the orchestral Suite persane by French composer André Caplet, evoking an exoticized Persian atmosphere.
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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a0cc8dc8819084ce125691b2bd7e |
completed | May 3, 2026, 7:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a387d0ea08c81908cc36e99b055c45f |
completed | June 22, 2026, 12:08 a.m. |
| NEDg | Description generation | batch_6a387da3cca88190871b690e2ee62c9e |
completed | June 22, 2026, 12:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a387e3b94cc8190bfc6b69d756793fb |
completed | June 22, 2026, 12:13 a.m. |
Created at: May 3, 2026, 4:05 p.m.