Triple
T36923548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delaney |
E913271
|
entity |
| Predicate | hasCommonRegionOfPrevalence |
P55272
|
FINISHED |
| Object | Ireland |
E5475
|
NE 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: Ireland | Statement: [Delaney, hasCommonRegionOfPrevalence, Ireland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonRegionOfPrevalence Context triple: [Delaney, hasCommonRegionOfPrevalence, Ireland]
-
A.
countryOrRegionOfPrevalence
chosen
Indicates the country or geographic region where something (such as a condition, practice, or phenomenon) is most commonly found or occurs most frequently.
-
B.
hasPrevalence
Indicates that something occurs or exists at a certain frequency, rate, or proportion within a defined population, group, or context.
-
C.
higherPrevalenceRegion
Indicates that a condition, characteristic, or phenomenon occurs more frequently in one region compared to another.
-
D.
prevalentIn
Indicates that something occurs frequently or is commonly found within a particular context, group, or environment.
-
E.
isEndemicTo
Indicates that something naturally occurs and is restricted to a particular geographic area or region.
- F. None of above.
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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a3e2c226f6881908738a1cf6f394f66 |
completed | June 26, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.