Triple
T36537420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delaware Interstate Highways |
E900625
|
entity |
| Predicate | hasConnectorRoute |
P204920
|
FINISHED |
| Object | Interstate 295 in Delaware |
E1690639
|
NE 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: Interstate 295 in Delaware | Statement: [Delaware Interstate Highways, hasConnectorRoute, Interstate 295 in Delaware]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConnectorRoute Context triple: [Delaware Interstate Highways, hasConnectorRoute, Interstate 295 in Delaware]
-
A.
hasConnector
Indicates that one entity is linked or joined to another entity through a connector or connecting element.
-
B.
hasPipelineConnection
Indicates that one entity is linked to another via a pipeline through which materials, fluids, or data can flow.
-
C.
hasRouteNetwork
Indicates that one entity possesses, is associated with, or is covered by a specific route network connecting multiple locations or paths.
-
D.
hasFlankingRoute
Indicates that one location or position can be reached or bypassed via an alternative side or rear route that avoids direct approach.
-
E.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
- F. None of above. chosen
Provenance (5 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_69f76e5fbb388190b70c4c15573c8143 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3c17142a348190be22c30f4e990216 |
completed | June 24, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c82f8c88190bd77a086023ac0e1 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:11 p.m.