Triple
T12670392
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | All of Me (film) |
E302661
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object | Me Too |
E302661
|
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: Me Too | Statement: [All of Me (film), basedOn, Me Too]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Me Too Context triple: [All of Me (film), basedOn, Me Too]
-
A.
Me Too
"Me Too" is a 2016 upbeat pop song by Meghan Trainor that celebrates self-confidence and body positivity.
-
B.
Me Too (novel)
chosen
Me Too is a novel whose story inspired the film "All of Me."
-
C.
Mr. Me Too
"Mr. Me Too" is a 2006 hip-hop single by Clipse featuring Pharrell Williams, known for its minimalist Neptunes production and sharp commentary on trend-chasing and imitation in rap culture.
-
D.
MeToo movement
The MeToo movement is a global social campaign against sexual harassment and assault that gained prominence in the late 2010s as survivors publicly shared their experiences and challenged systemic abuse of power.
-
E.
"Times Up"
"Times Up" is a critically acclaimed 1994 hip-hop single by rapper O.C., celebrated for its sharp lyricism and classic East Coast boom-bap production.
- 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_69d7bdee64a08190801c6d470aefd723 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96183a6048190b2ef219eb9d20aa4 |
completed | April 10, 2026, 8:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6688e101481909bc3b9e13ed84632 |
completed | May 2, 2026, 9:11 p.m. |
Created at: April 9, 2026, 5:20 p.m.