Triple
T8770615
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Tombeau de Couperin |
E208448
|
entity |
| Predicate | hasNoText |
P85299
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [Le Tombeau de Couperin, hasNoText, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoText Context triple: [Le Tombeau de Couperin, hasNoText, true]
-
A.
hasText
Indicates that an entity is associated with or contains a specific piece of textual content.
-
B.
hasTextElement
Indicates that an entity contains or is associated with a specific text-based component or segment.
-
C.
hasTextBy
Indicates that one entity (such as a document, work, or record) contains or is associated with text authored or written by another entity.
-
D.
hasTextualCharacter
Indicates that something possesses or exhibits the qualities of written or printed text, such as letters, symbols, or characters.
-
E.
hasNoChildren
Indicates that the subject entity does not have any children associated with it.
- F. None of above. chosen
Provenance (4 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_69ca835edb4481909b4aafb616dc5eb7 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f2b08f881909f3d4fab2eda1d67 |
completed | March 31, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cfddef48190aee764ee7b25bae9 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:41 p.m.