Triple
T21019998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Look into My Eyes |
E517779
|
entity |
| Predicate | chronologyNextTitle |
P26896
|
FINISHED |
| Object | If I Could Teach the World |
E517780
|
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: If I Could Teach the World | Statement: [Look into My Eyes, chronologyNextTitle, If I Could Teach the World]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: If I Could Teach the World Context triple: [Look into My Eyes, chronologyNextTitle, If I Could Teach the World]
-
A.
If I Could Teach the World
chosen
"If I Could Teach the World" is a socially conscious hip hop song by Bone Thugs-n-Harmony that reflects on violence, struggle, and the desire for peace and unity.
-
B.
The World I Live In
The World I Live In is a collection of essays by Helen Keller in which she vividly describes her inner life and sensory experiences as a deafblind person.
-
C.
Teach Me
"Teach Me" is a song featured on the album "Back to Me."
-
D.
Teach Me
Teach Me is a song featured on the album "All I Want Is You" by American singer-songwriter Miguel.
-
E.
What I've Learned
"What I've Learned" is a long-running Esquire magazine feature in which notable figures share personal insights, life lessons, and reflections in a first-person, quote-driven format.
- 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_69e0b50262b081909bc488937145eb73 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e6fc5c905c8190ba2f9f82b6cd1648 |
completed | April 21, 2026, 4:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a095a48166481908f6f178b9ff539a6 |
completed | May 17, 2026, 6:03 a.m. |
Created at: April 16, 2026, 1:54 p.m.