Triple
T4607565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yemeni rial |
E100473
|
entity |
| Predicate | hasFeatureOnBanknotes |
P57412
|
FINISHED |
| Object | images of Yemeni landmarks |
—
|
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: images of Yemeni landmarks | Statement: [Yemeni rial, hasFeatureOnBanknotes, images of Yemeni landmarks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFeatureOnBanknotes Context triple: [Yemeni rial, hasFeatureOnBanknotes, images of Yemeni landmarks]
-
A.
hasScriptOnBanknotes
Indicates that a currency’s banknotes contain written or printed script on them.
-
B.
hasBanknotes
Indicates that an entity possesses or contains one or more banknotes.
-
C.
issuesBanknotes
Indicates that an entity (typically a central bank or monetary authority) produces and puts banknotes into official circulation as legal tender.
-
D.
hasBanknotesIssuedBy
Indicates that one entity possesses or contains banknotes that were issued by another entity.
-
E.
lastSeriesBanknotesFeatured
Indicates that the referenced banknotes were the most recent series to prominently feature a particular subject or design.
- 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_69bd43cce1e08190a07d53af6a9b6c24 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd599debdc81909d11d0e871c666bb |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:12 p.m.