Triple
T5329009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Civil Lines, Bareilly |
E123256
|
entity |
| Predicate | roadPattern |
P1777
|
FINISHED |
| Object | broad tree-lined roads |
—
|
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: broad tree-lined roads | Statement: [Civil Lines, Bareilly, roadPattern, broad tree-lined roads]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roadPattern Context triple: [Civil Lines, Bareilly, roadPattern, broad tree-lined roads]
-
A.
roadFeature
chosen
Indicates that an entity is a specific physical or functional characteristic associated with a road, such as its structure, markings, or related infrastructure.
-
B.
roadSystem
Indicates a relationship where multiple roads are organized and connected as part of a larger, integrated transportation network or infrastructure.
-
C.
roadType
Indicates the classification or category of a road based on its functional or physical characteristics.
-
D.
roadTraverses
Indicates that a road passes through, crosses, or extends across a specified geographic area or feature.
-
E.
roadName
Indicates the specific name assigned to a road that identifies it within a transportation or address system.
- 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_69bd46477f9081909d242a327d749466 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8593bd6c8190b2054e548ddf2458 |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.