Triple
T17781181
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clothespin |
E443901
|
entity |
| Predicate | subjectHasForm |
P169
|
FINISHED |
| Object | oversized spring-type clothespin |
—
|
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: oversized spring-type clothespin | Statement: [Clothespin, subjectHasForm, oversized spring-type clothespin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectHasForm Context triple: [Clothespin, subjectHasForm, oversized spring-type clothespin]
-
A.
containsForm
Indicates that one entity includes or encapsulates another entity as a form, structure, or representation within it.
-
B.
hasForm
chosen
Indicates that one entity possesses, exhibits, or is characterized by a particular shape, structure, or configuration.
-
C.
usesForm
Indicates that one entity employs, applies, or operates through a particular form, format, or structured representation of something.
-
D.
hasCorrespondenceForm
Indicates that there exists a specific format, template, or structural representation used for the correspondence associated with an entity.
-
E.
subjectCanBe
Indicates that the subject has the potential or capability to assume, become, or be classified as the specified object or state.
- 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_69d8b9ef17708190bdf7e2adbf14ddc2 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4872152508190870a1765e0972ec1 |
completed | April 19, 2026, 7:41 a.m. |
| PD | Predicate disambiguation | batch_69e3d8d8e538819084f1584426b41d5e |
completed | April 18, 2026, 7:17 p.m. |
Created at: April 10, 2026, 10:12 a.m.