Triple
T18667021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love That Girl |
E456360
|
entity |
| Predicate | album |
P1995
|
FINISHED |
| Object | The Way I See It |
—
|
NE NERFINISHED |
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: The Way I See It | Statement: [Love That Girl, album, The Way I See It]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: The Way I See It Context triple: [Love That Girl, album, The Way I See It]
-
A.
The Way I See It
"The Way I See It" is a memoir by Patti Davis reflecting on her life as Ronald Reagan’s daughter and her complex family relationships.
-
B.
The Way I See It
chosen
The Way I See It is a retro-soul studio album by American musician Raphael Saadiq that pays homage to classic Motown and 1960s R&B sounds.
-
C.
What I See
"What I See" is a photography book by Brooklyn Beckham showcasing his personal images and visual perspective on his life and surroundings.
-
D.
When He Sees Me
"When He Sees Me" is a character-driven song from the musical *Waitress* that explores the anxieties and hopes surrounding dating and vulnerability.
-
E.
When You See Me
"When You See Me" is a crime thriller novel by Lisa Gardner that follows FBI profiler Kimberly Quincy and survivor-turned-vigilante Flora Dane as they uncover dark secrets tied to a serial killer’s past.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d38f72b4819090a935175d9ca8af |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e556ad88b481908bd008d469e878fd |
completed | April 19, 2026, 10:26 p.m. |
Created at: April 10, 2026, 11:48 a.m.