Triple
T23989338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CQL |
E605019
|
entity |
| Predicate | hasRelationExample |
P154528
|
FINISHED |
| Object | = |
—
|
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: = | Statement: [CQL, hasRelationExample, =]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelationExample Context triple: [CQL, hasRelationExample, =]
-
A.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
B.
testsRelation
Indicates a relationship where one entity evaluates, examines, or verifies another entity, typically to assess its properties, behavior, or correctness.
-
C.
hasShapeRelation
Indicates that one entity is related to another through a specific geometric or spatial shape relationship (such as similarity, congruence, or containment of shape).
-
D.
hasRelationships
Indicates that an entity is connected to one or more other entities through specified types of relationships.
-
E.
hasRelationSymbol
Indicates that there exists a specific relational operator or symbol used to denote the relationship between entities.
- 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_69e295463f7c8190b1c19dbd114641b9 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d38a40588190887c2abc6565bbf4 |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e348b548190b76e50f9b611f76d |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:37 p.m.