Triple
T27903583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Telangana–Maharashtra border |
E705705
|
entity |
| Predicate | hasTransportCrossingType |
P10712
|
FINISHED |
| Object | road bridges |
—
|
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 bridges | Statement: [Telangana–Maharashtra border, hasTransportCrossingType, road bridges]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransportCrossingType Context triple: [Telangana–Maharashtra border, hasTransportCrossingType, road bridges]
-
A.
hasTransportationCrossings
Indicates that one location or route includes points where transportation paths (such as roads, railways, or walkways) intersect or cross over/under another feature.
-
B.
crossingType
chosen
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
C.
hasBridgeTypeCrossing
Indicates that a bridge is characterized by a specific type of crossing it provides or supports.
-
D.
hasMajorCrossing
Indicates that one entity has a significant or primary intersection or crossing with another entity.
-
E.
hasBayCrossing
Indicates that one place is connected to another by a crossing over a bay, such as a bridge, tunnel, or ferry route.
- 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_69ef96b490ac8190a412d04c5d009f3e |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69fd3d46d1f48190a1b20dd063224b7d |
completed | May 8, 2026, 1:32 a.m. |
| PD | Predicate disambiguation | batch_69fd3ae1510c81908fe1280efc17feee |
completed | May 8, 2026, 1:22 a.m. |
Created at: April 27, 2026, 6:43 p.m.