Triple
T24857469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlos Argentino Daneri |
E622065
|
entity |
| Predicate | usesAlephFor |
P157415
|
FINISHED |
| Object | inspiration for his poem |
—
|
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: inspiration for his poem | Statement: [Carlos Argentino Daneri, usesAlephFor, inspiration for his poem]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAlephFor Context triple: [Carlos Argentino Daneri, usesAlephFor, inspiration for his poem]
-
A.
usesAlphabet
Indicates that one entity employs or is written using the alphabet or writing system associated with another entity.
-
B.
usesAlphabetResources
Indicates that an entity makes use of alphabet-related resources (such as letters, character sets, or alphabet-based tools) in performing an action or function.
-
C.
usesLibraryClassificationSystem
Indicates that an entity organizes or categorizes its materials according to a formal library classification system.
-
D.
isLendingLibrary
Indicates that an entity functions as a library that lends items (such as books or media) to users.
-
E.
libraryUsed
Indicates that one entity makes use of another entity as a software or code library to provide functionality or services.
- 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_69e2fac350d08190b3affde1b451a8c5 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f43043512481909501a3979cac9947 |
completed | May 1, 2026, 4:46 a.m. |
| PD | Predicate disambiguation | batch_69f420fd375c81908ea4a4e60b76ee8f |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f4303fad6c8190844f069164f0904d |
completed | May 1, 2026, 4:46 a.m. |
Created at: April 18, 2026, 5:21 a.m.