Triple
T1244104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quo Fata Ferunt |
E26724
|
entity |
| Predicate | hasPartOfSpeech |
P12863
|
FINISHED |
| Object | adverbial clause |
—
|
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: adverbial clause | Statement: [Quo Fata Ferunt, hasPartOfSpeech, adverbial clause]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPartOfSpeech Context triple: [Quo Fata Ferunt, hasPartOfSpeech, adverbial clause]
-
A.
grammaticalType
chosen
Indicates the grammatical category or role (such as part of speech or syntactic function) that an expression has within a language.
-
B.
hasNounClassSystem
Indicates that an entity possesses a grammatical system in which nouns are categorized into distinct classes that affect their agreement with other elements in the language.
-
C.
grammaticalForm
Indicates the specific grammatical structure or morphological form that an expression or word takes in a given linguistic context.
-
D.
lexicalItem
Indicates that one entity is a word or vocabulary unit associated with, or used to express, another entity (such as a concept, meaning, or linguistic entry).
-
E.
placeOfSpeech
Indicates the location where a speech or spoken event takes place.
- 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf636e208190a4d56806db61916c |
completed | March 1, 2026, 10:36 p.m. |
| PD | Predicate disambiguation | batch_69a4bb696a38819095845c84f0241287 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.