Triple
T34797529
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nords |
E1003131
|
entity |
| Predicate | alignmentTendency |
P16437
|
FINISHED |
| Object | honor-bound |
—
|
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: honor-bound | Statement: [Nords, alignmentTendency, honor-bound]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alignmentTendency Context triple: [Nords, alignmentTendency, honor-bound]
-
A.
alignedAgainst
Indicates that two or more entities are united in opposition to a common target, side, or objective.
-
B.
typicalAlignment
Indicates the usual or most common way in which two entities are positioned, oriented, or arranged relative to each other.
-
C.
alignmentConcept
chosen
Indicates a conceptual or abstract relationship of alignment or correspondence between entities, such as agreement, compatibility, or shared orientation in some dimension.
-
D.
alignmentGoal
Indicates that an entity has a desired or target alignment state it aims to achieve or maintain.
-
E.
alignmentRelation
Indicates that one entity is positioned, oriented, or arranged in a specific way relative to another entity.
- F. None of above.
Provenance (3 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_69f76db543808190b188c6c86a91491b |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77a86050881909fa363fe6984f79f |
completed | May 3, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69f7795b1abc8190823664d1caa94649 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.