Triple
T25756887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palermo |
E648624
|
entity |
| Predicate | dieShrinkOf |
P157998
|
FINISHED |
| Object | Paris core |
—
|
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: Paris core | Statement: [Palermo, dieShrinkOf, Paris core]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dieShrinkOf Context triple: [Palermo, dieShrinkOf, Paris core]
-
A.
dieShrinkOf
chosen
Indicates that one entity is a smaller, more advanced manufacturing process node derived from the other entity’s larger, earlier process node.
-
B.
rinkType
Indicates the specific kind or category of rink associated with an entity (e.g., ice rink, roller rink, practice rink).
-
C.
cutDown
Indicates that an agent causes something standing or elevated (such as a tree or structure) to fall or be reduced by cutting.
-
D.
collapsedDuring
Indicates that one entity structurally failed or fell down while another specified event or process was occurring.
-
E.
drop
Indicates that an entity causes something to fall or be released from a higher position to a lower one.
- 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_69e7ab314d788190b3abe19e114080e1 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f5fd83a8c08190a01a2ba975690e38 |
completed | May 2, 2026, 1:34 p.m. |
| PD | Predicate disambiguation | batch_69f4938262ac8190b41f922d0407d272 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 4:42 a.m.