Triple
T37880082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kenzan (needlepoint holders) |
E944841
|
entity |
| Predicate | placementMethod |
P98362
|
FINISHED |
| Object | stems are pressed onto spikes |
—
|
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: stems are pressed onto spikes | Statement: [kenzan (needlepoint holders), placementMethod, stems are pressed onto spikes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: placementMethod Context triple: [kenzan (needlepoint holders), placementMethod, stems are pressed onto spikes]
-
A.
placementType
chosen
Indicates the specific manner or category in which something is positioned, arranged, or assigned within a given context.
-
B.
alignmentMethod
Indicates the technique or procedure used to align one entity with another or with a reference standard.
-
C.
placementPolicyDeterminedBy
Indicates that the rules or strategy for placing something are defined or governed by a particular source, authority, or policy-setting entity.
-
D.
placementIn
Indicates that one entity is located or positioned within the spatial or structural bounds of another entity.
-
E.
canonicalPlacement
Indicates the standard or preferred position or arrangement of one entity relative to another within a defined structure or system.
- 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_69f76ef02668819089e7940c4001af5e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fe08d2b2e48190ac7be6d62d4a44a3 |
completed | May 8, 2026, 4:01 p.m. |
| PD | Predicate disambiguation | batch_69fe06cd3af08190ae25de0dc0cdd573 |
completed | May 8, 2026, 3:52 p.m. |
Created at: May 3, 2026, 4:19 p.m.