Triple
T1244108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quo Fata Ferunt |
E26724
|
entity |
| Predicate | numberOfMainVerb |
P25927
|
FINISHED |
| Object | third person plural |
—
|
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: third person plural | Statement: [Quo Fata Ferunt, numberOfMainVerb, third person plural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMainVerb Context triple: [Quo Fata Ferunt, numberOfMainVerb, third person plural]
-
A.
hasInfinitiveVerbEnding
Indicates that a verb takes the infinitive form with a specific infinitive verb ending (such as “-to” in English or “-en” in German).
-
B.
numberOfMainTexts
Indicates the quantity of primary or main textual components associated with an entity.
-
C.
numberOfGrammaticalCases
Indicates the relationship that specifies how many distinct grammatical cases a language or linguistic system possesses.
-
D.
hasGrammaticalNumber
Indicates that an expression is associated with a specific grammatical number category (such as singular, plural, or dual) in a language.
-
E.
hasVerseCount
Indicates that an entity (such as a text or section) is associated with a specific number of verses it contains.
- 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_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. |
| PDg | Predicate description generation | batch_69a4bce611ec819092cb13d354d0903e |
completed | March 1, 2026, 10:25 p.m. |
Created at: March 1, 2026, 7:47 p.m.