Triple
T12486287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anquan Boldin |
E298439
|
entity |
| Predicate | alsoKnownAs |
P39
|
FINISHED |
| Object |
Q
Q is the nickname of Anquan Boldin, a former NFL wide receiver known for his physical playing style and productivity with teams like the Arizona Cardinals and Baltimore Ravens.
|
E983457
|
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: Q | Statement: [Anquan Boldin, alsoKnownAs, Q]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Q Context triple: [Anquan Boldin, alsoKnownAs, Q]
-
A.
Q
The Q is a New York City Subway service that runs along the BMT Broadway Line in Manhattan and the Brighton Line in Brooklyn, providing crosstown and interborough transit.
-
B.
Q
Q is a powerful, omnipotent trickster from the Q Continuum who frequently tests and torments the crew of the USS Enterprise in Star Trek: The Next Generation.
-
C.
Q
Q is a recurring comedic character from the James Bond film series, known as the eccentric head of MI6's gadget and technology division.
-
D.
QUE
QUE is the station code for Queen station, a public transit stop in Toronto's subway system.
-
E.
QUE
QUE is the standard abbreviation used for the Quebec Remparts, a major junior ice hockey team in the Quebec Major Junior Hockey League.
- 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: Q Triple: [Anquan Boldin, alsoKnownAs, Q]
Generated description
Q is the nickname of Anquan Boldin, a former NFL wide receiver known for his physical playing style and productivity with teams like the Arizona Cardinals and Baltimore Ravens.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Q Target entity description: Q is the nickname of Anquan Boldin, a former NFL wide receiver known for his physical playing style and productivity with teams like the Arizona Cardinals and Baltimore Ravens.
-
A.
Q
The Q is a New York City Subway service that runs along the BMT Broadway Line in Manhattan and the Brighton Line in Brooklyn, providing crosstown and interborough transit.
-
B.
Q
Q is a recurring comedic character from the James Bond film series, known as the eccentric head of MI6's gadget and technology division.
-
C.
Q
Q is a powerful, omnipotent trickster from the Q Continuum who frequently tests and torments the crew of the USS Enterprise in Star Trek: The Next Generation.
-
D.
QUE
QUE is the station code for Queen station, a public transit stop in Toronto's subway system.
-
E.
QUE
QUE is the standard abbreviation used for the Quebec Remparts, a major junior ice hockey team in the Quebec Major Junior Hockey League.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94de077bc81908b5ff057a1bf2b4f |
completed | April 10, 2026, 7:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f63f2b5ed481909ead4f5b96d44064 |
completed | May 2, 2026, 6:15 p.m. |
| NEDg | Description generation | batch_69f6401199408190ad2657802afd93c9 |
completed | May 2, 2026, 6:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6416ba1bc8190a772bffe4d83ec15 |
completed | May 2, 2026, 6:24 p.m. |
Created at: April 8, 2026, 9:56 p.m.