Triple
T2570012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mingrelian language |
E57640
|
entity |
| Predicate | hasAlignment |
P39832
|
FINISHED |
| Object | nominative-accusative |
—
|
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: nominative-accusative | Statement: [Mingrelian language, hasAlignment, nominative-accusative]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAlignment Context triple: [Mingrelian language, hasAlignment, nominative-accusative]
-
A.
requiresAlignment
Indicates that one entity depends on another entity being properly aligned or brought into a specified alignment condition before the relationship or action can occur.
-
B.
alignsWith
Indicates that one entity is in agreement, harmony, or consistent correspondence with another in terms of position, direction, standard, or principle.
-
C.
hasRouteAlignment
Indicates that there is a defined spatial or geometric alignment associated with a route or pathway.
-
D.
alignedAgainst
Indicates that two or more entities are united in opposition to a common target, side, or objective.
-
E.
hasOrientation
Indicates that one entity is positioned or directed in a specific spatial or conceptual alignment relative to a reference frame or another entity.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd382928c8190b6316f3db48d8e73 |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd251b48c8190862c7b39ea1bf8ea |
completed | March 7, 2026, 7:22 a.m. |
Created at: March 6, 2026, 9:48 p.m.