Triple
T37118997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Metropolitan Branch Trail |
E919195
|
entity |
| Predicate | hasBicycleRouteNumber |
P144329
|
FINISHED |
| Object |
DC Bicycle Route 6
DC Bicycle Route 6 is a designated Washington, D.C. bicycle route that follows the Metropolitan Branch Trail corridor as part of the city’s signed bike network.
|
E2213435
|
NE FINISHED |
How this triple was built (3 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: DC Bicycle Route 6 | Statement: [Metropolitan Branch Trail, hasBicycleRouteNumber, DC Bicycle Route 6]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: DC Bicycle Route 6 Triple: [Metropolitan Branch Trail, hasBicycleRouteNumber, DC Bicycle Route 6]
Generated description
DC Bicycle Route 6 is a designated Washington, D.C. bicycle route that follows the Metropolitan Branch Trail corridor as part of the city’s signed bike network.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBicycleRouteNumber Context triple: [Metropolitan Branch Trail, hasBicycleRouteNumber, DC Bicycle Route 6]
-
A.
bikeway
chosen
Indicates that there is a designated path or route intended primarily for bicycle travel between locations.
-
B.
bikingTime
Indicates the duration or specific time period during which an entity engages in biking.
-
C.
hasBicycleAccessFrom
Indicates that a location or entity can be reached from another location or entity specifically via bicycle access.
-
D.
hasConnectingRoadNumber
Indicates that there exists a road connection between two locations or road segments identified by a specific road number.
-
E.
hasBicycleFacilities
Indicates that appropriate bicycle-related infrastructure or amenities are available at or associated with the subject.
- F. None of above.
Provenance (6 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_69f76e9c57148190ba789dd059645bb9 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fbc36ce1f88190a7fa1656b714e107 |
completed | May 6, 2026, 10:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3f6a198990819085ac8c903b6936e0 |
completed | June 27, 2026, 6:13 a.m. |
| NEDg | Description generation | batch_6a3f6b00a9788190b91e5ef4c2af8340 |
completed | June 27, 2026, 6:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a3f6b8877dc8190869db81917018452 |
completed | June 27, 2026, 6:19 a.m. |
| PD | Predicate disambiguation | batch_69fbbd13595c81908719f52c3d37a7e8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:15 p.m.