Triple
T22519729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roman Catholic Diocese of Tucson |
E556741
|
entity |
| Predicate | hasHistoricMissions |
P16530
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Roman Catholic Diocese of Tucson, hasHistoricMissions, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricMissions Context triple: [Roman Catholic Diocese of Tucson, hasHistoricMissions, yes]
-
A.
missionHistory
chosen
Indicates the record of past missions or assignments associated with an entity, including their occurrence and relevant details.
-
B.
numberOfSuccessfulMissions
Indicates the count of missions that have been completed successfully by the referenced entity or within the specified context.
-
C.
hasMissionIn
Indicates that an entity carries out, undertakes, or is assigned a mission within a specified location or region.
-
D.
spaceMissionsFlown
Indicates the number or specific instances of space missions that an entity has participated in or carried out.
-
E.
hasNamesakeMission
Indicates that one entity has a mission named after it or sharing its name.
- 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_69e11e5657e881909f16ca58352c50da |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15e30a96081909b8511d525518da1 |
completed | April 29, 2026, 1:26 a.m. |
| PD | Predicate disambiguation | batch_69ee625e3b408190a60c759fb0b28fe2 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 16, 2026, 8:50 p.m.