Triple
T33469436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coat of arms of the Lithuanian SSR |
E857144
|
entity |
| Predicate | positionOfWheatEars |
P199024
|
FINISHED |
| Object | sides |
—
|
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: sides | Statement: [Coat of arms of the Lithuanian SSR, positionOfWheatEars, sides]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOfWheatEars Context triple: [Coat of arms of the Lithuanian SSR, positionOfWheatEars, sides]
-
A.
numberOfRiceStalks
Indicates the quantity or count of rice stalks associated with a given entity or context.
-
B.
yieldRelativeToOryza sativa
Indicates the comparative yield performance of an entity relative to that of *Oryza sativa* (cultivated rice).
-
C.
isGrainCropRelative
Indicates that one entity is taxonomically or functionally related to a grain crop (e.g., a close relative or variant of a plant grown primarily for its grain).
-
D.
usesWheatAs
Indicates that one entity employs wheat in a specific role, function, or capacity (such as an ingredient, material, or resource).
-
E.
grain
Indicates that one entity is composed of or contains a granular substance or small particles of 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_69f34973461481909c701c98ebd75623 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69ff1ba8694481909ceb36f26ca85612 |
completed | May 9, 2026, 11:34 a.m. |
| PD | Predicate disambiguation | batch_69ff1b27f0f08190a9e74308c5b3d1ba |
completed | May 9, 2026, 11:31 a.m. |
| PDg | Predicate description generation | batch_69ff1ba7494481908678a7a0f93dbd03 |
completed | May 9, 2026, 11:33 a.m. |
Created at: May 1, 2026, 1:37 a.m.