Triple
T22111717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heriz |
E546432
|
entity |
| Predicate | rugCategory |
P70987
|
FINISHED |
| Object | village rugs |
—
|
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: village rugs | Statement: [Heriz, rugCategory, village rugs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rugCategory Context triple: [Heriz, rugCategory, village rugs]
-
A.
drugClass
Indicates that one entity is classified as a particular pharmacological or therapeutic category of drugs in relation to another entity.
-
B.
primaryDrug
Indicates that one drug is identified as the main or most important medication in a given treatment, context, or combination relative to other associated drugs.
-
C.
isGenderSpecificCategory
Indicates that the category applies specifically to one gender rather than being gender-neutral.
-
D.
categoryLabel_H
Indicates that an entity is assigned a human-readable category label or classification.
-
E.
categoryLabel_N
chosen
Indicates that an entity is assigned a specific categorical label or classification name.
- 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_69e11e38b3848190ac3a4fa97d56e65a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12949cc7881908898ca7dc130f57f |
completed | April 28, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69e71b2ed7348190b6fa2e52f54393fb |
completed | April 21, 2026, 6:37 a.m. |
Created at: April 16, 2026, 8:31 p.m.