Triple
T9304902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwynns Falls |
E223857
|
entity |
| Predicate | hasTributary |
P415
|
FINISHED |
| Object |
Dead Run
Dead Run is a small stream in Maryland that serves as a tributary within the Gwynns Falls watershed in the Baltimore area.
|
E790371
|
NE FINISHED |
How this triple was built (4 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: Dead Run | Statement: [Gwynns Falls, hasTributary, Dead Run]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dead Run Context triple: [Gwynns Falls, hasTributary, Dead Run]
-
A.
Suicide Run
"Suicide Run" is a collection of crime novellas by Michael Connelly featuring his iconic LAPD detective Harry Bosch.
-
B.
Thunder Run
Thunder Run is an indoor, mine train-style roller coaster at Canada's Wonderland that spirals through the park’s central mountain structure.
-
C.
Life on the Run
Life on the Run is a memoir by former NBA player and U.S. senator Bill Bradley that reflects on his basketball career and the personal and social lessons he drew from life in professional sports.
-
D.
Deadfall
Deadfall is a 1993 neo-noir crime thriller film known for its convoluted plot and an over-the-top performance by Nicolas Cage.
-
E.
Deadfall
"Deadfall" is a novel by American author Patti Davis, known for its psychological drama and exploration of complex family relationships.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Dead Run Triple: [Gwynns Falls, hasTributary, Dead Run]
Generated description
Dead Run is a small stream in Maryland that serves as a tributary within the Gwynns Falls watershed in the Baltimore area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dead Run Target entity description: Dead Run is a small stream in Maryland that serves as a tributary within the Gwynns Falls watershed in the Baltimore area.
-
A.
Suicide Run
"Suicide Run" is a collection of crime novellas by Michael Connelly featuring his iconic LAPD detective Harry Bosch.
-
B.
Thunder Run
Thunder Run is an indoor, mine train-style roller coaster at Canada's Wonderland that spirals through the park’s central mountain structure.
-
C.
Life on the Run
Life on the Run is a memoir by former NBA player and U.S. senator Bill Bradley that reflects on his basketball career and the personal and social lessons he drew from life in professional sports.
-
D.
Deadfall
Deadfall is a 1993 neo-noir crime thriller film known for its convoluted plot and an over-the-top performance by Nicolas Cage.
-
E.
Deadfall
"Deadfall" is a novel by American author Patti Davis, known for its psychological drama and exploration of complex family relationships.
- 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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd1da623ac81908bab6dfb1bbce25d |
completed | April 1, 2026, 1:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0b2735d788190bd8f963562fb85a8 |
completed | April 4, 2026, 6:40 a.m. |
| NEDg | Description generation | batch_69d0b4231b708190b8a4a342bc63e84d |
completed | April 4, 2026, 6:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d0b4b8131c8190b2aa8be56925b7bc |
completed | April 4, 2026, 6:50 a.m. |
Created at: March 30, 2026, 7:36 p.m.