Triple
T3458338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Norse morphology |
E72960
|
entity |
| Predicate | hasVerbClass |
P48361
|
FINISHED |
| Object | strong verb |
—
|
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: strong verb | Statement: [Old Norse morphology, hasVerbClass, strong verb]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVerbClass Context triple: [Old Norse morphology, hasVerbClass, strong verb]
-
A.
hasVerbAspect
Indicates that a verb or verbal expression is associated with a particular grammatical aspect (such as perfective, imperfective, or progressive) describing the temporal structure of the action or state.
-
B.
hasInfinitiveVerbEnding
Indicates that a verb takes the infinitive form with a specific infinitive verb ending (such as “-to” in English or “-en” in German).
-
C.
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.
-
D.
associatedWithVerb
Indicates that one entity is connected or linked to another through some verb-based relationship or action.
-
E.
numberOfMainVerb
Indicates the count of main verbs present in a given clause, sentence, or linguistic unit.
- 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_69ad85b12a908190a1d10a6b03b4f8ae |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adbae36e748190bf20fd3c6de22e19 |
completed | March 8, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69adae041d588190a84a02bca94adec8 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed74ecc8190b74dc70ab59a3e1c |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:16 p.m.