Triple
T6646401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lule Sami language |
E150710
|
entity |
| Predicate | hasMoodDistinctions |
P72018
|
FINISHED |
| Object | indicative and imperative |
—
|
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: indicative and imperative | Statement: [Lule Sami language, hasMoodDistinctions, indicative and imperative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoodDistinctions Context triple: [Lule Sami language, hasMoodDistinctions, indicative and imperative]
-
A.
hasMoodCategory
Indicates that an entity is associated with a particular mood classification or emotional category.
-
B.
hasMood
Indicates that an entity is experiencing or characterized by a particular emotional or affective state.
-
C.
hasMoodSystem
Indicates that an entity possesses or is associated with a system responsible for managing or representing moods or emotional states.
-
D.
hasDefinitenessDistinction
Indicates that a language or system grammatically distinguishes between definite and indefinite (or otherwise specified) reference in its expressions.
-
E.
hasTypeOfEmotion
Indicates that an entity experiences, expresses, or is associated with a particular kind or category of emotion.
- 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_69c687f1a3048190828b7342f7125d5c |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9c6cb0819084fec8e0beb430de |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad04d66c8190926ffcbff372643b |
completed | March 27, 2026, 4:15 p.m. |
| PDg | Predicate description generation | batch_69c6cc988c0081909d22b86ca299331c |
completed | March 27, 2026, 6:29 p.m. |
Created at: March 27, 2026, 2 p.m.