Triple
T14992106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playland Amusement Park |
E373859
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object | Kiddyland |
E176307
|
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: Kiddyland | Statement: [Playland Amusement Park, hasPart, Kiddyland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiddyland Context triple: [Playland Amusement Park, hasPart, Kiddyland]
-
A.
Kiddyland
chosen
Kiddyland is a children’s amusement area within Playland Park featuring kid-friendly rides and attractions.
-
B.
Kid 'n Play
Kid 'n Play is a late-1980s and early-1990s American hip hop duo best known for their upbeat party rap, signature dance moves, and the House Party film series.
-
C.
Toyland
Toyland is the colorful, whimsical fantasy world that serves as the primary setting for Enid Blyton’s Noddy stories, inhabited by living toys and playful characters.
-
D.
Babyland
Babyland is a family-friendly area within Bear Country USA where visitors can observe and learn about young and newborn animals in a safe, accessible setting.
-
E.
Kiddy Smile
Kiddy Smile is a French DJ, producer, and vogue-house musician known for his role in Paris’s ballroom scene and for blending club culture with outspoken LGBTQ+ activism.
- 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_69d85ccc84388190aa151e5173370c8d |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded715db408190b44e8a8452c79764 |
completed | April 15, 2026, 12:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe969842848190a030db797c851fed |
completed | May 9, 2026, 2:06 a.m. |
Created at: April 10, 2026, 2:53 a.m.