Triple
T36483533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alouette |
E898878
|
entity |
| Predicate | teachesVocabularyFor |
P21344
|
FINISHED |
| Object | body parts |
—
|
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: body parts | Statement: [Alouette, teachesVocabularyFor, body parts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teachesVocabularyFor Context triple: [Alouette, teachesVocabularyFor, body parts]
-
A.
learnsLanguageFrom
Indicates that one entity acquires or improves knowledge of a language through instruction, exposure, or guidance provided by another entity.
-
B.
learnedIn
Indicates that an entity acquired knowledge, skills, or information within a particular context, environment, or source.
-
C.
teachesCharactersFrom
Indicates that one entity instructs or educates another entity using characters (such as letters, symbols, or written forms) as the teaching content.
-
D.
languageOfTeachings
Indicates the language in which teachings, lessons, or instructional content are delivered or expressed.
-
E.
teachesAbout
chosen
Indicates that one entity provides instruction or information to another entity on a particular subject or topic.
- F. None of above.
Provenance (3 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_69f76e5a0e088190a2b6706aeb41723c |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:10 p.m.