Triple
T19242511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pygmalion of Tyre |
E481166
|
entity |
| Predicate | languageOfReception |
P48590
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Pygmalion of Tyre, languageOfReception, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfReception Context triple: [Pygmalion of Tyre, languageOfReception, Latin]
-
A.
languageOfExpression
Indicates that a particular language is used as the medium or form in which an expression (such as a text, utterance, or work) is realized.
-
B.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
C.
languageOfTransmission
Indicates the language used to convey or transmit the content or information in a given communication or resource.
-
D.
languageOfInterpretation
chosen
Indicates the language in which something (such as text, speech, or content) is interpreted or understood.
-
E.
languageOfWorkRecognized
Indicates that a work is officially recognized as being created or expressed in a particular language.
- 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faf2353c819094a9a1af3a858715 |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dcfae6f081909cc173cf71a5005c |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:27 p.m.