Triple
T24715841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic Archdiocese of Dublin |
E612157
|
entity |
| Predicate | isSecondCitySeeAfter |
P60666
|
FINISHED |
| Object | Archdiocese of Armagh |
—
|
NE NERFINISHED |
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: Archdiocese of Armagh | Statement: [Roman Catholic Archdiocese of Dublin, isSecondCitySeeAfter, Archdiocese of Armagh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSecondCitySeeAfter Context triple: [Roman Catholic Archdiocese of Dublin, isSecondCitySeeAfter, Archdiocese of Armagh]
-
A.
hasSecondaryCity
Indicates that an entity possesses or is associated with a secondary city in addition to its primary city.
-
B.
secondarySeeCity
Indicates that an entity has a secondary or less prominent association with a particular city.
-
C.
secondMetropolitan
chosen
Indicates that one entity is the second metropolitan (e.g., second-ranking or second-designated metropolitan authority or see) in relation to another entity.
-
D.
otherCity
Indicates that one city is different from and not the same as another city.
-
E.
isSecondMostPopulousCityIn
Indicates that a city is the second most populous city within a specified larger region or country.
- 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_69e2d7d6e7a48190bb43b0d8bb1137a0 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ee8ada8819089a7016b50308ff0 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:36 a.m.