Triple
T20224751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chartres-style labyrinth |
E495347
|
entity |
| Predicate | hasNumberOfQuadrants |
P27279
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Chartres-style labyrinth, hasNumberOfQuadrants, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfQuadrants Context triple: [Chartres-style labyrinth, hasNumberOfQuadrants, 4]
-
A.
hasQuadrants
chosen
Indicates that something is divided into four distinct sections or regions, typically arranged as quadrants.
-
B.
hasQuadrantRole
Indicates that an entity holds a specific functional or positional role within a defined quadrant of a larger structure or system.
-
C.
isQuadrangleOf
Indicates that one entity is a four-sided polygon (quadrilateral) that has the other entity as its defining instance or member.
-
D.
quadrangleNumber
Indicates that the subject is associated with a specific quadrangle identifier or index within a partitioned spatial or structural system.
-
E.
hasCornerCount
Indicates that an entity is associated with a specific number of corners.
- 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_69da626cff80819097b530718a7c98b6 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66fd8f1948190adbb947a7870bb43 |
completed | April 20, 2026, 6:26 p.m. |
| PD | Predicate disambiguation | batch_69e55b18609481909ab28bc8750a642f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:39 p.m.