Triple
T18156372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mirabeau |
E434640
|
entity |
| Predicate | hasCornerType |
P109336
|
FINISHED |
| Object | right-hand corner |
—
|
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: right-hand corner | Statement: [Mirabeau, hasCornerType, right-hand corner]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCornerType Context triple: [Mirabeau, hasCornerType, right-hand corner]
-
A.
hasTypeOfCorner
chosen
Indicates that one entity possesses or is characterized by a specific kind or category of corner.
-
B.
hasCorner
Indicates that one entity possesses or includes a corner that is part of or associated with another entity.
-
C.
hasCornerCount
Indicates that an entity is associated with a specific number of corners.
-
D.
hasSlowCorners
Indicates that an entity possesses corners or turning points that are navigated or traversed at a relatively low speed.
-
E.
hasBoundaryType
Indicates that one entity has a boundary characterized by a specific type or classification in relation to another entity or context.
- 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_69d8b90b7a188190b3fc7b8d4a6cd20a |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4debe27a88190bd76c6f78fcf1bd1 |
completed | April 19, 2026, 1:55 p.m. |
| PD | Predicate disambiguation | batch_69e43317d11c81908d1dc14921566b47 |
completed | April 19, 2026, 1:42 a.m. |
Created at: April 10, 2026, 10:30 a.m.