Triple
T2224520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WaterWorld: A Live Sea War Spectacular |
E48617
|
entity |
| Predicate | usesEffectType |
P37149
|
FINISHED |
| Object | fire effects |
—
|
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: fire effects | Statement: [WaterWorld: A Live Sea War Spectacular, usesEffectType, fire effects]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesEffectType Context triple: [WaterWorld: A Live Sea War Spectacular, usesEffectType, fire effects]
-
A.
specialEffectsBy
Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
-
B.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
C.
usesToolType
Indicates that an entity performs an action or fulfills a role by employing a specific type or category of tool.
-
D.
notableEffect
Indicates that one entity has a significant impact, consequence, or influence on another entity or situation.
-
E.
usedAgainst
Indicates that one entity is employed, applied, or deployed in opposition to, or for the purpose of affecting, another entity.
- 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_69a88aa51b388190949868ec9766e587 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc03ec3788190b5ae32201364f7ab |
completed | March 7, 2026, 6:05 a.m. |
| PD | Predicate disambiguation | batch_69abbdac31d8819092d17815e11921e9 |
completed | March 7, 2026, 5:54 a.m. |
| PDg | Predicate description generation | batch_69abbfe93d7c81909f1b9c1b1e3c7989 |
completed | March 7, 2026, 6:04 a.m. |
Created at: March 4, 2026, 7:47 p.m.