Triple
T5787537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plum Run |
E128304
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object |
Triangular Field
Triangular Field is a historic battlefield area at Gettysburg, Pennsylvania, known for intense fighting during the American Civil War.
|
E549267
|
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: Triangular Field | Statement: [Plum Run, flowsNear, Triangular Field]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Triangular Field Context triple: [Plum Run, flowsNear, Triangular Field]
-
A.
Fields Corner
Fields Corner is a rapid transit station in Dorchester, Boston, serving as a key stop on the Massachusetts Bay Transportation Authority’s Red Line.
-
B.
Brown Field
Brown Field is a military training area associated with the United States Marine Corps Officer Candidates School.
-
C.
The Great Field
The Great Field is an ancient Egyptian royal burial ground on the west bank of the Nile at Luxor, renowned for its rock-cut tombs of New Kingdom pharaohs and nobles.
-
D.
Trávniky
Trávniky is a residential neighborhood within the Ružinov borough of Bratislava, Slovakia.
-
E.
Smallfield
Smallfield is a village in Surrey, England, situated near the town of Horley and close to Gatwick Airport.
- 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: Triangular Field Triple: [Plum Run, flowsNear, Triangular Field]
Generated description
Triangular Field is a historic battlefield area at Gettysburg, Pennsylvania, known for intense fighting during the American Civil War.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Triangular Field Target entity description: Triangular Field is a historic battlefield area at Gettysburg, Pennsylvania, known for intense fighting during the American Civil War.
-
A.
Fields Corner
Fields Corner is a rapid transit station in Dorchester, Boston, serving as a key stop on the Massachusetts Bay Transportation Authority’s Red Line.
-
B.
Brown Field
Brown Field is a military training area associated with the United States Marine Corps Officer Candidates School.
-
C.
The Great Field
The Great Field is an ancient Egyptian royal burial ground on the west bank of the Nile at Luxor, renowned for its rock-cut tombs of New Kingdom pharaohs and nobles.
-
D.
Trávniky
Trávniky is a residential neighborhood within the Ružinov borough of Bratislava, Slovakia.
-
E.
Smallfield
Smallfield is a village in Surrey, England, situated near the town of Horley and close to Gatwick Airport.
- 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_69c0084450048190bc647b649a05136b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a5297c88190bd28adb2552a26f4 |
completed | March 22, 2026, 5:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0981a002c8190ac8ed7407a80919c |
completed | March 23, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69c0989f7e58819098175e6eaacdb9ee |
completed | March 23, 2026, 1:34 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c09cf3220481908c52b519e8495fff |
completed | March 23, 2026, 1:52 a.m. |
Created at: March 22, 2026, 3:51 p.m.