Triple
T2581239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capital University |
E57094
|
entity |
| Predicate | athleticsNickname |
P55
|
FINISHED |
| Object |
Comets
The Comets are the athletic teams representing Capital University in intercollegiate sports.
|
E280177
|
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: Comets | Statement: [Capital University, athleticsNickname, Comets]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Comets Context triple: [Capital University, athleticsNickname, Comets]
-
A.
Comet
Comet is one of Santa Claus’s traditional flying reindeer, often depicted as swift and spirited as he helps pull Santa’s sleigh on Christmas Eve.
-
B.
Komet
Komet was the nickname of the Messerschmitt Me 163, a German World War II rocket-powered interceptor aircraft known for its extraordinary speed and unconventional design.
-
C.
Dibiasky comet
The Dibiasky comet is the fictional, Earth-destroying comet central to the plot of the satirical disaster film "Don't Look Up."
-
D.
Oort cloud
The Oort cloud is a distant, spherical shell of icy bodies surrounding the Solar System, thought to be the source of many long-period comets.
-
E.
Kuiper Belt objects
Kuiper Belt objects are icy celestial bodies orbiting the Sun beyond Neptune, thought to be remnants from the early solar system and the source of many short-period comets.
- 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: Comets Triple: [Capital University, athleticsNickname, Comets]
Generated description
The Comets are the athletic teams representing Capital University in intercollegiate sports.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Comets Target entity description: The Comets are the athletic teams representing Capital University in intercollegiate sports.
-
A.
Comet
Comet is one of Santa Claus’s traditional flying reindeer, often depicted as swift and spirited as he helps pull Santa’s sleigh on Christmas Eve.
-
B.
Komet
Komet was the nickname of the Messerschmitt Me 163, a German World War II rocket-powered interceptor aircraft known for its extraordinary speed and unconventional design.
-
C.
Dibiasky comet
The Dibiasky comet is the fictional, Earth-destroying comet central to the plot of the satirical disaster film "Don't Look Up."
-
D.
Oort cloud
The Oort cloud is a distant, spherical shell of icy bodies surrounding the Solar System, thought to be the source of many long-period comets.
-
E.
Kuiper Belt objects
Kuiper Belt objects are icy celestial bodies orbiting the Sun beyond Neptune, thought to be remnants from the early solar system and the source of many short-period comets.
- 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_69ab4a4dca6481908c301f8e317396e7 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3c6da888190ba7abfe37d182602 |
completed | March 7, 2026, 7:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af657cc2b08190a9055d6da7744851 |
completed | March 10, 2026, 12:27 a.m. |
| NEDg | Description generation | batch_69af69a66078819084f341b052860751 |
completed | March 10, 2026, 12:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af6a071f1c8190b2a707a0c98ddc94 |
completed | March 10, 2026, 12:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.