Triple
T25768082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Derisha |
E648936
|
entity |
| Predicate | hasLexicalRelationWith |
P9129
|
FINISHED |
| Object | Perisha |
—
|
NE NERFINISHED |
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: Perisha | Statement: [Derisha, hasLexicalRelationWith, Perisha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLexicalRelationWith Context triple: [Derisha, hasLexicalRelationWith, Perisha]
-
A.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
-
B.
hasLexicalInfluenceOn
chosen
Indicates that one linguistic element (such as a word, phrase, or lexicon) has affected or shaped the form, usage, or meaning of another linguistic element.
-
C.
hasTypologicalRelation
Indicates a relationship where two linguistic entities are connected based on shared structural or typological features, such as word order, morphology, or phonological patterns.
-
D.
ridgeRelation
Indicates a relationship in which one entity is a ridge or forms a ridge-like structural feature relative to another entity.
-
E.
allyRelation
Indicates a cooperative, supportive relationship in which the entities act as allies toward shared or aligned goals.
- 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_69e7ab322db0819092d6a2b3d4572e01 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c1f94ac8190bc6fbc7916fc0d82 |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 22, 2026, 5:12 a.m.