Triple
T5319390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blame the Vain |
E121633
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Lucky That Way
"Lucky That Way" is a song featured on the album "Blame the Vain" by American country musician Dwight Yoakam.
|
E511525
|
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: Lucky That Way | Statement: [Blame the Vain, hasTrack, Lucky That Way]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lucky That Way Context triple: [Blame the Vain, hasTrack, Lucky That Way]
-
A.
Lucky Day
Lucky Day is one of the three bumbling silent-film actors who mistakenly become real-life heroes in the comedy film "Three Amigos."
-
B.
Lucky Guy
Lucky Guy is a Broadway play by Nora Ephron that dramatizes the career of New York tabloid columnist Mike McAlary.
-
C.
Lucky Town
Lucky Town is a 1992 rock album by Bruce Springsteen that blends heartland rock with introspective, personal songwriting.
-
D.
The Lucky One
The Lucky One is a romantic drama film based on a Nicholas Sparks novel, following a U.S. Marine who seeks out a woman he believes was his good-luck charm during the war.
-
E.
To-Lucky
To-Lucky is one of the official mascots of Japan’s Hanshin Tigers baseball team, typically depicted as a cheerful anthropomorphic tiger supporting the club at games and events.
- 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: Lucky That Way Triple: [Blame the Vain, hasTrack, Lucky That Way]
Generated description
"Lucky That Way" is a song featured on the album "Blame the Vain" by American country musician Dwight Yoakam.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lucky That Way Target entity description: "Lucky That Way" is a song featured on the album "Blame the Vain" by American country musician Dwight Yoakam.
-
A.
Lucky Day
Lucky Day is one of the three bumbling silent-film actors who mistakenly become real-life heroes in the comedy film "Three Amigos."
-
B.
Lucky Guy
Lucky Guy is a Broadway play by Nora Ephron that dramatizes the career of New York tabloid columnist Mike McAlary.
-
C.
Lucky Town
Lucky Town is a 1992 rock album by Bruce Springsteen that blends heartland rock with introspective, personal songwriting.
-
D.
The Lucky One
The Lucky One is a romantic drama film based on a Nicholas Sparks novel, following a U.S. Marine who seeks out a woman he believes was his good-luck charm during the war.
-
E.
To-Lucky
To-Lucky is one of the official mascots of Japan’s Hanshin Tigers baseball team, typically depicted as a cheerful anthropomorphic tiger supporting the club at games and events.
- 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_69bd463d956c819088105c3db802c017 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd855407048190bcdb97c7098cc2aa |
completed | March 20, 2026, 5:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf18a117d48190a7fb45be0b002f4e |
completed | March 21, 2026, 10:16 p.m. |
| NEDg | Description generation | batch_69bf197733b48190910bdd60fbd94fff |
completed | March 21, 2026, 10:19 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf19e1b064819091851e975f83e781 |
completed | March 21, 2026, 10:21 p.m. |
Created at: March 20, 2026, 1:59 p.m.