Triple
T3294289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Super Bowl XLVII |
E69174
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
HarBowl
HarBowl is the popular nickname for Super Bowl XLVII, which featured a historic matchup between head coach brothers Jim and John Harbaugh.
|
E343780
|
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: HarBowl | Statement: [Super Bowl XLVII, nickname, HarBowl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: HarBowl Context triple: [Super Bowl XLVII, nickname, HarBowl]
-
A.
Blunder Bowl
Blunder Bowl is a derisive nickname for Super Bowl V, remembered for its unusually high number of turnovers and mistakes despite being a championship game.
-
B.
Stupor Bowl
Stupor Bowl is a derisive nickname for Super Bowl V, reflecting its reputation as a poorly played, mistake-filled championship game.
-
C.
Soccer Bowl
Soccer Bowl is the championship match that determined the season winner of the modern North American Soccer League.
-
D.
Sugar Bowl
The Sugar Bowl is one of college football’s oldest and most prestigious postseason bowl games, traditionally held in New Orleans and often featuring top-ranked teams.
-
E.
Horseshoe
Horseshoe is a well-known casino and racetrack brand in the United States, recognized for its gambling, entertainment, and hospitality offerings.
- 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: HarBowl Triple: [Super Bowl XLVII, nickname, HarBowl]
Generated description
HarBowl is the popular nickname for Super Bowl XLVII, which featured a historic matchup between head coach brothers Jim and John Harbaugh.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: HarBowl Target entity description: HarBowl is the popular nickname for Super Bowl XLVII, which featured a historic matchup between head coach brothers Jim and John Harbaugh.
-
A.
Blunder Bowl
Blunder Bowl is a derisive nickname for Super Bowl V, remembered for its unusually high number of turnovers and mistakes despite being a championship game.
-
B.
Stupor Bowl
Stupor Bowl is a derisive nickname for Super Bowl V, reflecting its reputation as a poorly played, mistake-filled championship game.
-
C.
Soccer Bowl
Soccer Bowl is the championship match that determined the season winner of the modern North American Soccer League.
-
D.
Sugar Bowl
The Sugar Bowl is one of college football’s oldest and most prestigious postseason bowl games, traditionally held in New Orleans and often featuring top-ranked teams.
-
E.
Horseshoe
Horseshoe is a well-known casino and racetrack brand in the United States, recognized for its gambling, entertainment, and hospitality offerings.
- 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_69ad859d45748190b0742408c954b39f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb07661748190bf57469e101c5283 |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2e86b8e04819091f4a4ae6d6a87ad |
completed | March 12, 2026, 4:23 p.m. |
| NEDg | Description generation | batch_69b2e8f6a7c48190bc457f348c3a7179 |
completed | March 12, 2026, 4:25 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b2e986dcc88190bd3daa6c6fdcb50e |
completed | March 12, 2026, 4:27 p.m. |
Created at: March 8, 2026, 3:10 p.m.