Triple
T1921625
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Working on a Dream |
E40136
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Good Eye
"Good Eye" is a song by Bruce Springsteen featured on his 2009 rock album *Working on a Dream*.
|
E217026
|
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: Good Eye | Statement: [Working on a Dream, hasTrack, Good Eye]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Good Eye Context triple: [Working on a Dream, hasTrack, Good Eye]
-
A.
Doctor My Eyes
"Doctor My Eyes" is a 1972 soft rock song by Jackson Browne, known for its introspective lyrics and distinctive piano-driven melody.
-
B.
The Eyeopener
The Eyeopener is an independent student-run newspaper serving the Toronto Metropolitan University community with campus news, commentary, and features.
-
C.
Red Eye
Red Eye is a 2005 psychological thriller film in which Cillian Murphy plays a charming but menacing terrorist who coerces a hotel manager during a tense overnight flight.
-
D.
Blink
Blink is an open-source web browser engine developed primarily by Google and used in several major browsers to render web pages.
-
E.
Big Eyes
Big Eyes is a 2014 biographical drama film directed by Tim Burton that tells the story of painter Margaret Keane and the legal battle over the credit for her distinctive big-eyed children paintings.
- 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: Good Eye Triple: [Working on a Dream, hasTrack, Good Eye]
Generated description
"Good Eye" is a song by Bruce Springsteen featured on his 2009 rock album *Working on a Dream*.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Good Eye Target entity description: "Good Eye" is a song by Bruce Springsteen featured on his 2009 rock album *Working on a Dream*.
-
A.
Doctor My Eyes
"Doctor My Eyes" is a 1972 soft rock song by Jackson Browne, known for its introspective lyrics and distinctive piano-driven melody.
-
B.
The Eyeopener
The Eyeopener is an independent student-run newspaper serving the Toronto Metropolitan University community with campus news, commentary, and features.
-
C.
Red Eye
Red Eye is a 2005 psychological thriller film in which Cillian Murphy plays a charming but menacing terrorist who coerces a hotel manager during a tense overnight flight.
-
D.
Blink
Blink is an open-source web browser engine developed primarily by Google and used in several major browsers to render web pages.
-
E.
Big Eyes
Big Eyes is a 2014 biographical drama film directed by Tim Burton that tells the story of painter Margaret Keane and the legal battle over the credit for her distinctive big-eyed children paintings.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb233011881908736523d36f01b0c |
completed | March 7, 2026, 5:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adf3e458e8819098ea1c2d5598f890 |
completed | March 8, 2026, 10:10 p.m. |
| NEDg | Description generation | batch_69adf4cd91008190ada815601d9f76b4 |
completed | March 8, 2026, 10:14 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adf5681ea88190979237322fd2785b |
completed | March 8, 2026, 10:17 p.m. |
Created at: March 4, 2026, 7:35 p.m.