Triple
T23237010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Calle del Codo |
E581328
|
entity |
| Predicate | hasBendShape |
P52595
|
FINISHED |
| Object | elbow-shaped |
—
|
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: elbow-shaped | Statement: [Calle del Codo, hasBendShape, elbow-shaped]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBendShape Context triple: [Calle del Codo, hasBendShape, elbow-shaped]
-
A.
hasNumberOfPrebends
Indicates the relationship specifying how many prebends (stipendiary church positions or benefices) are associated with a given entity.
-
B.
bendAngle
Indicates the degree to which one part is bent relative to another, typically measured as the angle formed at their joint or intersection.
-
C.
hasBulgeType
Indicates the specific kind or classification of bulge associated with an entity.
-
D.
hasHairpinBends
chosen
Indicates that a route, road, or path includes very sharp, U-shaped turns resembling hairpins.
-
E.
hasBulge
Indicates that one entity possesses or exhibits a protruding or swollen part relative to its surrounding surface or structure.
- 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_69e2460556f88190be1744a84a84173f |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f192e98dec8190a23385600bed9ae0 |
completed | April 29, 2026, 5:11 a.m. |
| PD | Predicate disambiguation | batch_69effcdadec0819092ec1749ee453b4e |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:09 p.m.