Triple
T14350422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apollo Kids |
E355836
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Ynot |
E1062929
|
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: Ynot | Statement: [Apollo Kids, producer, Ynot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ynot Context triple: [Apollo Kids, producer, Ynot]
-
A.
Ynot
chosen
Ynot is a film production company known for its work on the acclaimed Mexican romantic drama "Like Water for Chocolate."
-
B.
Notsi
Notsi is an Oceanic language spoken in parts of Papua New Guinea, belonging to the Meso-Melanesian branch of the Austronesian language family.
-
C.
Noth
Noth is a surname most prominently associated with American actor Chris Noth, known for his roles in television series such as "Sex and the City" and "Law & Order."
-
D.
Nebelong
Nebelong is a Danish surname most notably associated with 19th-century architect Johan Henrik Nebelong.
-
E.
Neyo
Ne-Yo is an American R&B singer, songwriter, and record producer known for hits like "So Sick" and "Closer" and for writing songs for numerous major artists.
- 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_69d82790a7e08190877e2d349b2e8d8e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8f4e1e588190bdc7aaf7a2819948 |
completed | April 14, 2026, 7:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd4c4335e481909d4db39b8d25edc9 |
completed | May 8, 2026, 2:36 a.m. |
Created at: April 10, 2026, 1:14 a.m.