Triple
T13592205
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi–Mumbai Expressway |
E324718
|
entity |
| Predicate | hasTrafficManagementSystem |
P18246
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Delhi–Mumbai Expressway, hasTrafficManagementSystem, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTrafficManagementSystem Context triple: [Delhi–Mumbai Expressway, hasTrafficManagementSystem, yes]
-
A.
hasTrafficManagement
chosen
Indicates that an entity implements, uses, or is associated with systems or measures for controlling and optimizing traffic flow.
-
B.
hasTrafficControl
Indicates that some form of traffic management or regulation mechanism is present or applied to a given route, intersection, or transportation element.
-
C.
hasTrafficRegime
Indicates that a specified traffic control or regulatory system applies to a given road, area, or transport context.
-
D.
hasTrafficControlCenter
Indicates that an entity possesses or is served by a traffic control center responsible for monitoring and managing traffic operations.
-
E.
hasTrafficMonitoring
Indicates that an entity is equipped with or associated with a system or capability for observing, measuring, or analyzing traffic conditions or flows.
- 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_69d80769eaf081909d82f44e484d6113 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb056ce088190a6feb4266633d18b |
completed | April 12, 2026, 2:46 p.m. |
| PD | Predicate disambiguation | batch_69dbae18eaf48190809e8b365856cde9 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:49 p.m.