Triple
T38327363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copse |
E1036824
|
entity |
| Predicate | hasCornerDirection |
P204603
|
FINISHED |
| Object | right-hand |
—
|
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 | Statement: [Copse, hasCornerDirection, right-hand]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCornerDirection Context triple: [Copse, hasCornerDirection, right-hand]
-
A.
hasCorner
Indicates that one entity possesses or includes a corner that is part of or associated with another entity.
-
B.
hasCornerCount
Indicates that an entity is associated with a specific number of corners.
-
C.
hasCornerStructure
Indicates that one entity possesses or includes a structural element specifically located at or forming a corner of something.
-
D.
hasTypeOfCorner
Indicates that one entity possesses or is characterized by a specific kind or category of corner.
-
E.
hasBorderDirection
Indicates that one entity’s border lies in, or is oriented toward, a specified cardinal or relative direction with respect to another entity.
- 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_69f76e1c16fc8190bde982289dd5106b |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.