Triple
T13400570
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Turning Torso |
E319815
|
entity |
| Predicate | segmentDescription |
P17710
|
FINISHED |
| Object | nine five-storey pentagonal segments |
—
|
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: nine five-storey pentagonal segments | Statement: [Turning Torso, segmentDescription, nine five-storey pentagonal segments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: segmentDescription Context triple: [Turning Torso, segmentDescription, nine five-storey pentagonal segments]
-
A.
trackDescription
Indicates the descriptive information or summary text associated with a specific track (such as a song, audio piece, or recorded segment).
-
B.
routeDescription
Indicates a textual explanation or summary of the path, course, or itinerary taken between locations.
-
C.
transportSegment
Indicates a distinct portion of a larger journey or route during which something or someone is transported from one point to another.
-
D.
curveDescription
Indicates that a curve is characterized or defined by a specific descriptive text or explanation.
-
E.
segmentStructure
chosen
Indicates that one entity represents a structural or organizational subdivision (a segment) within the overall structure of 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_69d806b943cc8190b6af624d385d7e12 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbae47e99081909d8b5dba97a11988 |
completed | April 12, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69d9a0355de48190bb3fb96912e20df3 |
completed | April 11, 2026, 1:13 a.m. |
Created at: April 9, 2026, 9:34 p.m.