Triple
T7028103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maren Morris |
E163199
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Girl
"Girl" is a 2019 country-pop song by Maren Morris that serves as an empowering anthem about self-acceptance and resilience.
|
E637590
|
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: Girl | Statement: [Maren Morris, notableWork, Girl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Girl Context triple: [Maren Morris, notableWork, Girl]
-
A.
Girl
"Girl" is Pharrell Williams' 2014 funk- and R&B-infused studio album known for its upbeat, soulful sound and the hit single "Happy."
-
B.
Girl
"Girl" is a 2005 pop-rock song by American musician Beck, known for its catchy melody and surreal, collage-style lyrics.
-
C.
Girl
"Girl" is a reflective, acoustic-driven song by the Beatles from their 1965 album Rubber Soul, noted for its melancholic tone and introspective lyrics.
-
D.
Girls
"Girls" is a song by the Beastie Boys from their influential debut album "Licensed to Ill," known for its minimalist production and controversial, tongue-in-cheek lyrics about gender roles.
-
E.
Girls
Girls is an HBO comedy-drama television series created by and starring Lena Dunham that follows a group of young women navigating life and relationships in New York City.
- 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: Girl Triple: [Maren Morris, notableWork, Girl]
Generated description
"Girl" is a 2019 country-pop song by Maren Morris that serves as an empowering anthem about self-acceptance and resilience.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Girl Target entity description: "Girl" is a 2019 country-pop song by Maren Morris that serves as an empowering anthem about self-acceptance and resilience.
-
A.
Girl
"Girl" is Pharrell Williams' 2014 funk- and R&B-infused studio album known for its upbeat, soulful sound and the hit single "Happy."
-
B.
Girl
"Girl" is a 2005 pop-rock song by American musician Beck, known for its catchy melody and surreal, collage-style lyrics.
-
C.
Girl
"Girl" is a reflective, acoustic-driven song by the Beatles from their 1965 album Rubber Soul, noted for its melancholic tone and introspective lyrics.
-
D.
Girls
"Girls" is a song by the Beastie Boys from their influential debut album "Licensed to Ill," known for its minimalist production and controversial, tongue-in-cheek lyrics about gender roles.
-
E.
Girls
Girls is an HBO comedy-drama television series created by and starring Lena Dunham that follows a group of young women navigating life and relationships in New York City.
- 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_69c6885d691c81908cf7d31083113886 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e1fee32081908eff988b18daa6d0 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7758c87908190bd1ddcfdccc171b5 |
completed | March 28, 2026, 6:30 a.m. |
| NEDg | Description generation | batch_69c77a01c7b48190b022c6d2ecda7488 |
completed | March 28, 2026, 6:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c77a83ed8881908907bedcf6d6ea84 |
completed | March 28, 2026, 6:51 a.m. |
Created at: March 27, 2026, 2:35 p.m.