Triple
T2137565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Carter |
E46689
|
entity |
| Predicate | nickname |
P55
|
FINISHED |
| Object |
DC
DC is the widely used nickname of Dan Carter, the legendary New Zealand rugby union fly-half regarded as one of the greatest players in the sport’s history.
|
E237225
|
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: DC | Statement: [Dan Carter, nickname, DC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DC Context triple: [Dan Carter, nickname, DC]
-
A.
DC
DC is the standard two-letter U.S. postal abbreviation for the District of Columbia, the federal district containing the nation’s capital, Washington.
-
B.
DC Comics
DC Comics is a major American comic book publisher best known for iconic superhero characters such as Superman, Batman, and Wonder Woman.
-
C.
DC Entertainment
DC Entertainment is a media company and subsidiary of Warner Bros. responsible for managing and developing film, television, and other adaptations of DC Comics properties.
-
D.
DCU
DCU is the common abbreviation for D.C. United, a professional Major League Soccer club based in Washington, D.C.
-
E.
DC Universe
The DC Universe is a fictional superhero setting featuring characters like Superman, Batman, and Wonder Woman who coexist and interact across interconnected stories and worlds.
- 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: DC Triple: [Dan Carter, nickname, DC]
Generated description
DC is the widely used nickname of Dan Carter, the legendary New Zealand rugby union fly-half regarded as one of the greatest players in the sport’s history.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: DC Target entity description: DC is the widely used nickname of Dan Carter, the legendary New Zealand rugby union fly-half regarded as one of the greatest players in the sport’s history.
-
A.
DC
DC is the standard two-letter U.S. postal abbreviation for the District of Columbia, the federal district containing the nation’s capital, Washington.
-
B.
DC Comics
DC Comics is a major American comic book publisher best known for iconic superhero characters such as Superman, Batman, and Wonder Woman.
-
C.
DC Entertainment
DC Entertainment is a media company and subsidiary of Warner Bros. responsible for managing and developing film, television, and other adaptations of DC Comics properties.
-
D.
DCU
DCU is the common abbreviation for D.C. United, a professional Major League Soccer club based in Washington, D.C.
-
E.
DC Universe
The DC Universe is a fictional superhero setting featuring characters like Superman, Batman, and Wonder Woman who coexist and interact across interconnected stories and worlds.
- 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_69a88a174ab48190a5db20c132e5dccf |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abbdff9254819094d27405478e29a0 |
completed | March 7, 2026, 5:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae51af1e708190b63418da77776084 |
completed | March 9, 2026, 4:50 a.m. |
| NEDg | Description generation | batch_69ae5322097c81909d77d54ae258ab1a |
completed | March 9, 2026, 4:57 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5365cd808190aa8363b612ef0ec5 |
completed | March 9, 2026, 4:58 a.m. |
Created at: March 4, 2026, 7:44 p.m.