Triple
T13771013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Archbishop of Buenos Aires |
E330879
|
entity |
| Predicate | rankInCountry |
P110883
|
FINISHED |
| Object | primatial see de facto |
—
|
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: primatial see de facto | Statement: [Archbishop of Buenos Aires, rankInCountry, primatial see de facto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rankInCountry Context triple: [Archbishop of Buenos Aires, rankInCountry, primatial see de facto]
-
A.
rankingInCountry
Indicates the position or level an entity holds within an ordered list specific to a particular country.
-
B.
countryRanking
Indicates the relative position or rank assigned to a country within a specific ordered list or comparative evaluation.
-
C.
countryRankContext
Indicates the relative position or ranking of a country within a specified contextual framework (such as economic, political, or performance-based criteria).
-
D.
populationRank
Indicates the relative position of an entity in an ordered list based on the size of its population.
-
E.
countryRankingContext
Indicates the contextual framework or criteria under which a country's ranking is determined or interpreted.
- 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_69d81c583b0081909e408a17db517a21 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0235aea881909ab4c721db081b00 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe97846c819093b00ea117b64e0d |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59db0148190bcaf9646403ca64f |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 10:10 p.m.