Triple
T19516283
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | OK K.O.! Let's Be Heroes |
E488285
|
entity |
| Predicate | includesShorts |
P136211
|
FINISHED |
| Object | true |
—
|
LITERAL 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: true | Statement: [OK K.O.! Let's Be Heroes, includesShorts, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesShorts Context triple: [OK K.O.! Let's Be Heroes, includesShorts, true]
-
A.
appearsInShort
Indicates that an entity appears or is featured in a short-form work, such as a short film, short episode, or brief media piece.
-
B.
hasShort
Indicates that an entity possesses or is characterized by something of short length or duration.
-
C.
includesShow
Indicates that one entity contains or features a particular show as part of its content or offerings.
-
D.
isShort
Indicates that one entity has a relatively small height, length, or duration compared to a standard or to other entities.
-
E.
hasCinematicShort
Indicates that an entity is associated with or includes a cinematic short film or short-form cinematic content.
- F. None of above. chosen
Provenance (4 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6359ca7648190804c4d655170fda3 |
completed | April 20, 2026, 2:18 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7bd25881908caa04eaef1f6718 |
completed | April 19, 2026, 4:06 p.m. |
| PDg | Predicate description generation | batch_69e5004d3a708190a1c13c8f644f3926 |
completed | April 19, 2026, 4:18 p.m. |
Created at: April 10, 2026, 1:40 p.m.