Triple
T36315169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mellifont Abbey |
E894169
|
entity |
| Predicate | firstOfTypeInCountry |
P59622
|
FINISHED |
| Object | first Cistercian monastery in Ireland |
—
|
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: first Cistercian monastery in Ireland | Statement: [Mellifont Abbey, firstOfTypeInCountry, first Cistercian monastery in Ireland]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstOfTypeInCountry Context triple: [Mellifont Abbey, firstOfTypeInCountry, first Cistercian monastery in Ireland]
-
A.
firstForCountry
chosen
Indicates that the subject is the first instance or occurrence of its type to happen or exist within the specified country.
-
B.
hasCountryType
Indicates that an entity is associated with or classified under a specific type or category of country.
-
C.
firstMatchCountry
Indicates that the referenced country is the first one that matches a given set of criteria or conditions among a group of countries.
-
D.
firstOfType
Indicates that the subject is the earliest or initial instance of its kind within a specified group, category, or sequence.
-
E.
usedInCountryType
Indicates that something is utilized or applied within a specific type or category of country (e.g., developing, industrialized, etc.).
- 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_69f76e4d1a788190a6ab6ccca28547a7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8d06cc8190ab6a5e18d9d2571e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0a54cc8190868c1bfa1590d1a6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:09 p.m.