Triple
T14561497
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line D (Strasbourg tramway) |
E341675
|
entity |
| Predicate | hasPriorityUse |
P89945
|
FINISHED |
| Object | daily commuting |
—
|
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: daily commuting | Statement: [Line D (Strasbourg tramway), hasPriorityUse, daily commuting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPriorityUse Context triple: [Line D (Strasbourg tramway), hasPriorityUse, daily commuting]
-
A.
identifiesAsPriorityUses
chosen
Indicates that one entity designates or treats another entity as a priority for use or utilization.
-
B.
supportsPriority
Indicates that one entity provides functionality or capability for handling or honoring priority levels associated with another entity or operation.
-
C.
hasPriorityAt
Indicates that one entity holds a specified level of priority or precedence at a particular time, place, or context relative to others.
-
D.
hasPriorityIssue
Indicates that an entity is associated with an issue that is marked as high or urgent priority.
-
E.
hasUsageLevel
Indicates the degree or intensity with which something is used or utilized.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb389d0f48190a1d9d69456d1cbe1 |
completed | April 14, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69de5c57489c8190b57917be1dba6ae6 |
completed | April 14, 2026, 3:25 p.m. |
Created at: April 10, 2026, 1:23 a.m.