Triple
T26988661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Penny |
E679801
|
entity |
| Predicate | restrainedBy |
P22102
|
FINISHED |
| Object | straightjacket |
—
|
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: straightjacket | Statement: [Penny, restrainedBy, straightjacket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: restrainedBy Context triple: [Penny, restrainedBy, straightjacket]
-
A.
constrainedBy
Indicates that one entity’s state, behavior, or possibilities are limited, restricted, or governed by another entity.
-
B.
restraintType
chosen
Indicates the specific kind or method of restraint applied in a given situation or relationship.
-
C.
designedToConstrain
Indicates that one entity is intentionally created or configured to limit, restrict, or control the behavior, range, or properties of another entity.
-
D.
usesRestraints
Indicates that one entity applies or employs physical or procedural restraints on another entity.
-
E.
restraintPurpose
Indicates that one entity is used to restrain another entity for a specific purpose or intended outcome.
- 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_69eeeb5138ac8190b3c273ddc659a54f |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f6218de4ec81908d3001e5b8748c7d |
completed | May 2, 2026, 4:08 p.m. |
| PD | Predicate disambiguation | batch_69f61b3ee7b08190a0a1bc5d26b757aa |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 6:50 a.m.