Triple
T11341406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Broadview station |
E268604
|
entity |
| Predicate | hasSurfaceConnections |
P98602
|
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: [Broadview station, hasSurfaceConnections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurfaceConnections Context triple: [Broadview station, hasSurfaceConnections, yes]
-
A.
hasSurfaceConnection
Indicates that two entities are directly connected or in contact at their surfaces, allowing interaction or continuity between them.
-
B.
hasSurfaceSections
Indicates that an entity is composed of or divided into distinct sections or parts of its surface.
-
C.
hasSurfaceBody
Indicates that one entity possesses or is characterized by a particular surface or outer body.
-
D.
hasBorderConnection
Indicates that two regions or entities share a common boundary or are directly connected along a border.
-
E.
hasSurfaceBuilding
Indicates that one entity possesses or is associated with a building located on its surface.
- F. None of above. chosen
Provenance (4 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_69d6aacb1f0881908c84a349fd1be047 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea01c6c08190910a6ce8fb7e186d |
completed | April 9, 2026, 6:03 p.m. |
| PD | Predicate disambiguation | batch_69d787afe5a48190b8af1a3e19529641 |
completed | April 9, 2026, 11:04 a.m. |
| PDg | Predicate description generation | batch_69d796d120808190afff7154afa56c76 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:33 p.m.