Triple
T34775879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wings and Waves Waterpark |
E1002503
|
entity |
| Predicate | materializedFrom |
P151192
|
FINISHED |
| Object | conversion of Boeing 747 into slide platform |
—
|
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: conversion of Boeing 747 into slide platform | Statement: [Wings and Waves Waterpark, materializedFrom, conversion of Boeing 747 into slide platform]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: materializedFrom Context triple: [Wings and Waves Waterpark, materializedFrom, conversion of Boeing 747 into slide platform]
-
A.
materializationLocation
Indicates the place or setting where something comes into physical existence or is brought into a concrete form.
-
B.
materialFormedIn
Indicates that a material is created, produced, or formed within a specified process, environment, or context.
-
C.
materialSource
Indicates that one entity serves as the origin or provider of the material or substance used by another entity.
-
D.
isProducedFrom
chosen
Indicates that something is created, generated, or derived from a specified source or input.
-
E.
hasSourceMaterial
Indicates that something is derived from, based on, or created using a particular source material.
- F. None of above.
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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f782f4f10081908f97f6d0d2dbeec7 |
completed | May 3, 2026, 5:16 p.m. |
| PD | Predicate disambiguation | batch_69f780ff71cc8190a67e71076fbad81a |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 3:59 p.m.