Triple
T14658910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Good Morning Aztlán |
E344182
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Get to This |
E982561
|
NE FINISHED |
How this triple was built (2 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: Get to This | Statement: [Good Morning Aztlán, hasPart, Get to This]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Get to This Context triple: [Good Morning Aztlán, hasPart, Get to This]
-
A.
Come Get to This
chosen
"Come Get to This" is an upbeat soul track by Marvin Gaye featured on his landmark 1973 album "Let's Get It On."
-
B.
Get to You
"Get to You" is a song featured on Davido's 2019 Afrobeats album *A Good Time*.
-
C.
Come and Get It
Come and Get It is the second solo studio album by British pop singer Rachel Stevens, noted for its polished dance-pop production and critical acclaim.
-
D.
Come and Get It
Come and Get It is a 1936 American drama film, co-directed by Howard Hawks and William Wyler, best known for featuring Walter Brennan in an Oscar-winning supporting performance.
-
E.
From There to Here
From There to Here is a British television drama series that follows a Manchester family whose lives are transformed by the 1996 IRA bombing and the social changes that follow.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb51b6a248190a44050c0e0ec2d16 |
completed | April 14, 2026, 9:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5e01cd081909c71fdcf67c3b1f5 |
completed | May 8, 2026, 12:24 p.m. |
Created at: April 10, 2026, 1:27 a.m.