Triple
T10068136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris–Washington route |
E213149
|
entity |
| Predicate | serviceMedium |
P91931
|
FINISHED |
| Object | air transportation |
—
|
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: air transportation | Statement: [Paris–Washington route, serviceMedium, air transportation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: serviceMedium Context triple: [Paris–Washington route, serviceMedium, air transportation]
-
A.
tradeMedium
Indicates that one entity serves as the medium or instrument through which another entity conducts trade or exchange transactions.
-
B.
targetMedium
Indicates the medium or channel through which an action, message, or effect is directed or intended to be delivered.
-
C.
applicationMedium
Indicates the medium or channel through which an application is submitted or communicated (e.g., online, paper, email).
-
D.
canonicalMedium
Indicates the primary or standard medium through which something is most authoritatively or typically expressed, distributed, or experienced.
-
E.
serviceIn
Indicates that one entity serves, operates, or performs its function within the context, scope, or domain of 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_69ca83977128819084084eb7d1d8c52a |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdcff798bc8190a84af7bedea66f0a |
completed | April 2, 2026, 2:09 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.