Triple
T175049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ontario |
E3554
|
entity |
| Predicate | containsLandmark |
P1098
|
FINISHED |
| Object |
Big Nickel
Big Nickel is a giant nine-metre-tall replica of a 1951 Canadian nickel and a famous roadside attraction located in Sudbury, Ontario.
|
E22043
|
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: Big Nickel | Statement: [Ontario, containsLandmark, Big Nickel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Big Nickel Context triple: [Ontario, containsLandmark, Big Nickel]
-
A.
Horseshoe
Horseshoe is a well-known casino and racetrack brand in the United States, recognized for its gambling, entertainment, and hospitality offerings.
-
B.
The Ball
The Ball is the popular nickname for Reunion Tower, a distinctive geodesic observation tower and Dallas landmark known for its glowing spherical top.
-
C.
California Gold
California Gold is a distinctive shade of gold used as one of the official school colors representing the University of California, Berkeley.
-
D.
Big Blue
Big Blue is the widely used nickname for the New York Giants, a professional American football team in the NFL.
-
E.
The Big Operator
The Big Operator is a 1959 American crime drama film starring Mickey Rooney as a corrupt union boss, notable for featuring Maila Nurmi in a supporting role.
- 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: Big Nickel Triple: [Ontario, containsLandmark, Big Nickel]
Generated description
Big Nickel is a giant nine-metre-tall replica of a 1951 Canadian nickel and a famous roadside attraction located in Sudbury, Ontario.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Big Nickel Target entity description: Big Nickel is a giant nine-metre-tall replica of a 1951 Canadian nickel and a famous roadside attraction located in Sudbury, Ontario.
-
A.
Horseshoe
Horseshoe is a well-known casino and racetrack brand in the United States, recognized for its gambling, entertainment, and hospitality offerings.
-
B.
The Ball
The Ball is the popular nickname for Reunion Tower, a distinctive geodesic observation tower and Dallas landmark known for its glowing spherical top.
-
C.
California Gold
California Gold is a distinctive shade of gold used as one of the official school colors representing the University of California, Berkeley.
-
D.
Big Blue
Big Blue is the widely used nickname for the New York Giants, a professional American football team in the NFL.
-
E.
The Big Operator
The Big Operator is a 1959 American crime drama film starring Mickey Rooney as a corrupt union boss, notable for featuring Maila Nurmi in a supporting role.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a25bafd5808190a0a0cb2b21ce007f |
completed | Feb. 28, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a2eb7babec8190a1c1a6bcc94605ef |
completed | Feb. 28, 2026, 1:19 p.m. |
| NEDg | Description generation | batch_69a2ec72092c8190bcc1efa7c0644560 |
completed | Feb. 28, 2026, 1:24 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69a2ecba99cc8190a85dd5e9c531a6e3 |
completed | Feb. 28, 2026, 1:25 p.m. |
Created at: Feb. 28, 2026, 2:39 a.m.