Triple
T10068704
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chandelier Tree |
E213162
|
entity |
| Predicate | tunnelAllows |
P91932
|
FINISHED |
| Object | cars to drive through trunk |
—
|
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: cars to drive through trunk | Statement: [Chandelier Tree, tunnelAllows, cars to drive through trunk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tunnelAllows Context triple: [Chandelier Tree, tunnelAllows, cars to drive through trunk]
-
A.
usesTunnel
Indicates that one entity makes use of a tunnel as a passage or route to reach or connect to another entity.
-
B.
hasTunnel
Indicates that one entity possesses, contains, or is connected by a tunnel to another entity.
-
C.
tunnelType
Indicates the specific kind or classification of a tunnel associated with an entity.
-
D.
tunnels
Indicates that one entity passes through, under, or within another entity via a tunnel-like passage or structure.
-
E.
hasTunnelShape
Indicates that something possesses a form or configuration resembling a tunnel, typically elongated, enclosed, and passage-like.
- 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff8d9c08190bc030f1dcc696310 |
completed | April 2, 2026, 2:10 a.m. |
| PD | Predicate disambiguation | batch_69cd4b92573481909389bc6148ae7ea8 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8d9b888190b8067bd916dae773 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 8:58 p.m.