Triple
T16371183
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | She Was Too Good to Me |
E397566
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object |
Tangerine
"Tangerine" is a jazz standard frequently interpreted by prominent jazz musicians and vocalists.
|
E1208429
|
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: Tangerine | Statement: [She Was Too Good to Me, hasTrack, Tangerine]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tangerine Context triple: [She Was Too Good to Me, hasTrack, Tangerine]
-
A.
Tangerine
Tangerine is a popular Afro-pop song by Nigerian singer Yemi Alade, known for its upbeat rhythm and vibrant, danceable style.
-
B.
Tangerine
"Tangerine" is a song by the English indie rock band Glass Animals, known for its dreamy production and introspective lyrics.
-
C.
Tangerine
"Tangerine" is a funk-infused hip hop track by Big Boi featuring T.I., known for its playful, club-ready sound and appearance on Big Boi’s debut solo album.
-
D.
Tangerine
"Tangerine" is an episode of the American sitcom "The King of Queens," known for its comedic take on everyday married life in Queens, New York.
-
E.
Paradise Road
Paradise Road is a 1997 war drama film about women prisoners of war in World War II, known for its ensemble cast and portrayal of resilience under Japanese captivity.
- 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: Tangerine Triple: [She Was Too Good to Me, hasTrack, Tangerine]
Generated description
"Tangerine" is a jazz standard frequently interpreted by prominent jazz musicians and vocalists.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tangerine Target entity description: "Tangerine" is a jazz standard frequently interpreted by prominent jazz musicians and vocalists.
-
A.
Tangerine
Tangerine is a popular Afro-pop song by Nigerian singer Yemi Alade, known for its upbeat rhythm and vibrant, danceable style.
-
B.
Tangerine
"Tangerine" is a song by the English indie rock band Glass Animals, known for its dreamy production and introspective lyrics.
-
C.
Tangerine
"Tangerine" is a funk-infused hip hop track by Big Boi featuring T.I., known for its playful, club-ready sound and appearance on Big Boi’s debut solo album.
-
D.
Tangerine
"Tangerine" is an episode of the American sitcom "The King of Queens," known for its comedic take on everyday married life in Queens, New York.
-
E.
Paradise Road
Paradise Road is a 1997 war drama film about women prisoners of war in World War II, known for its ensemble cast and portrayal of resilience under Japanese captivity.
- 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_69d87f2778dc8190aa95c7572db127e6 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e2ff420d04819096ff12e08edf2f8b |
completed | April 18, 2026, 3:49 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a002dc44c508190bf87b437d1447db6 |
completed | May 10, 2026, 7:03 a.m. |
| NEDg | Description generation | batch_6a002f7203d88190834594b03d29b193 |
completed | May 10, 2026, 7:10 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a002fd7fba8819095bb67c7e7a0fefd |
completed | May 10, 2026, 7:12 a.m. |
Created at: April 10, 2026, 5:08 a.m.