Triple
T13180040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orcus |
E313697
|
entity |
| Predicate | linguisticInfluence |
P108920
|
FINISHED |
| Object | name used as a common noun for the underworld in Late Latin contexts |
—
|
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: name used as a common noun for the underworld in Late Latin contexts | Statement: [Orcus, linguisticInfluence, name used as a common noun for the underworld in Late Latin contexts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linguisticInfluence Context triple: [Orcus, linguisticInfluence, name used as a common noun for the underworld in Late Latin contexts]
-
A.
languageInfluence
Indicates that one language has an effect on the development, usage, or characteristics of another language.
-
B.
languageOfInfluence
Indicates a relationship where one language has influenced the development, usage, or characteristics of another language.
-
C.
influencesLanguageOf
Indicates that one entity affects, shapes, or alters the language used by another entity.
-
D.
influencedLanguage
Indicates that one language has had an effect on the development, structure, or usage of another language.
-
E.
shareLanguageInfluence
Indicates that two entities affect or shape each other’s language use, development, or characteristics through mutual or shared influence.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc2c0c88190be357811aa8e828d |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98ceeb22c8190a6be666031d9e5a4 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 9, 2026, 9:14 p.m.