Triple
T37880070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | kenzan (needlepoint holders) |
E944841
|
entity |
| Predicate | supportsDesignPrinciple |
P204443
|
FINISHED |
| Object | precise stem placement |
—
|
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: precise stem placement | Statement: [kenzan (needlepoint holders), supportsDesignPrinciple, precise stem placement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsDesignPrinciple Context triple: [kenzan (needlepoint holders), supportsDesignPrinciple, precise stem placement]
-
A.
supportsPrinciple
Indicates that one entity endorses, upholds, or actively backs a particular principle or doctrine.
-
B.
designPrinciplesInclude
Indicates that a set of design principles contains or incorporates specific principles as part of it.
-
C.
implementsPrinciple
Indicates that an entity applies, follows, or puts into practice a specified principle in its design, behavior, or operation.
-
D.
usesPrinciple
Indicates that one entity applies, relies on, or is based upon a particular principle in its functioning, reasoning, or design.
-
E.
coversPrinciple
Indicates that one entity explains, addresses, or includes the fundamental concept or rule represented by 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_69f76ef02668819089e7940c4001af5e |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a192a008190a9917688a9e804f4 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:19 p.m.