Triple
T24439353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Puntila |
E616216
|
entity |
| Predicate | treatsMattiAs |
P156140
|
FINISHED |
| Object | friend when drunk |
—
|
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: friend when drunk | Statement: [Puntila, treatsMattiAs, friend when drunk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: treatsMattiAs Context triple: [Puntila, treatsMattiAs, friend when drunk]
-
A.
treatsRightAs
Indicates that one entity provides medical or therapeutic treatment to another entity who is identified as the right-hand participant in the relationship.
-
B.
seesMaatAs
Indicates that one entity regards or recognizes another entity as embodying or representing Maat (truth, justice, and cosmic order).
-
C.
treatmentOf
Indicates a relationship where one entity administers, provides, or is responsible for a therapeutic intervention directed toward another entity (typically a patient or condition).
-
D.
treatsHumansAs
Indicates how one entity regards or behaves toward humans, characterizing them in a particular way (e.g., as equals, tools, resources, or threats).
-
E.
treatsAsSubject
Indicates that one entity regards, handles, or processes another entity in the role or capacity of a subject (e.g., topic, focus, or primary object of consideration).
- 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_69e2d7ec44b081909ccaf1f3bbec0641 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f297891f108190a98e55c900494d30 |
completed | April 29, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69f287d3237c819099559c00f83131d8 |
completed | April 29, 2026, 10:36 p.m. |
| PDg | Predicate description generation | batch_69f28f4d978c81908310c01def2514cc |
completed | April 29, 2026, 11:07 p.m. |
Created at: April 18, 2026, 2:17 a.m.