Triple
T22012594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cecil Shorts III |
E543614
|
entity |
| Predicate | hasSurname |
P18
|
FINISHED |
| Object | Shorts |
—
|
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: Shorts | Statement: [Cecil Shorts III, hasSurname, Shorts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Shorts Context triple: [Cecil Shorts III, hasSurname, Shorts]
-
A.
Shorts
chosen
Shorts is a surname shared by various individuals, including American football player Cecil Shorts III.
-
B.
Shorts
"Shorts" is a 2009 family fantasy-comedy film directed by Robert Rodriguez that tells interconnected stories centered around a magical wish-granting rock in a suburban town.
-
C.
YouTube Shorts
YouTube Shorts is YouTube’s short-form vertical video platform designed for quick, snackable content similar to TikTok and Instagram Reels.
-
D.
Digital Short
Digital Short is a series of pre-recorded comedic video segments that became a signature part of Saturday Night Live, often featuring experimental sketches, music videos, and celebrity cameos.
-
E.
Shorts Competition
Shorts Competition is a dedicated program within the Tallinn Black Nights Film Festival that showcases and awards outstanding short films from around the world.
- 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_69e11e2db934819095556760c7d85e4d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a5e624819082ed5beeb4bc82fa |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:22 p.m.