Triple
T27859751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mira-Bhayandar Municipal Transport |
E704190
|
entity |
| Predicate | transportSubsector |
P1379
|
FINISHED |
| Object | road transport |
—
|
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: road transport | Statement: [Mira-Bhayandar Municipal Transport, transportSubsector, road transport]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transportSubsector Context triple: [Mira-Bhayandar Municipal Transport, transportSubsector, road transport]
-
A.
transportationSector
Indicates a relationship where an entity is involved in, associated with, or classified as part of the transportation sector or transportation-related activities.
-
B.
transportDevelopment
Indicates the development or improvement of transportation systems, infrastructure, or services connecting places or entities.
-
C.
transports
Indicates that one entity carries or conveys another entity from one place to another.
-
D.
transportType
chosen
Indicates the mode or means of transportation used in carrying something or someone from one place to another.
-
E.
transportContribution
Indicates that an entity contributes resources, effort, or support toward the transportation of something or someone.
- 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_69ef840e614c8190a88cf9638c14a265 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: April 27, 2026, 6:17 p.m.