Triple
T11150814
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1984 Summer Olympics women's individual all-around |
E263777
|
entity |
| Predicate | apparatusIncluded |
P22070
|
FINISHED |
| Object | vault |
—
|
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: vault | Statement: [1984 Summer Olympics women's individual all-around, apparatusIncluded, vault]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apparatusIncluded Context triple: [1984 Summer Olympics women's individual all-around, apparatusIncluded, vault]
-
A.
describesApparatus
chosen
Indicates that one entity provides a description or specification of an apparatus used by another entity or within a particular context.
-
B.
hasAuxiliaryEquipment
Indicates that one entity is equipped with, or accompanied by, additional supporting equipment associated with another entity.
-
C.
fleetIncludes
Indicates that a particular fleet contains or is composed of the specified entity or entities as its members.
-
D.
hardwareIncluded
Indicates that certain hardware components are provided or come bundled together with another item or product.
-
E.
equippedFor
Indicates that one entity is suitably provided with the necessary tools, features, or capabilities to perform a particular function or handle a specific situation for another entity or purpose.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8719e74819095413abc6c79296c |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.