Triple
T28156664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L. Nelson Bell |
E714767
|
entity |
| Predicate | workedAsMedicalMissionaryIn |
P166864
|
FINISHED |
| Object | China |
—
|
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: China | Statement: [L. Nelson Bell, workedAsMedicalMissionaryIn, China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workedAsMedicalMissionaryIn Context triple: [L. Nelson Bell, workedAsMedicalMissionaryIn, China]
-
A.
sentAsMissionaryBy
Indicates that one entity is formally commissioned and dispatched by another entity to serve as a missionary.
-
B.
hasNotableMissionary
Indicates that an entity is associated with, or has, a notable missionary linked to it.
-
C.
missionaryOrganization
Indicates that an entity is a religious or faith-based organization dedicated to missionary work or activities.
-
D.
missionaryRegion
Indicates that an entity carries out or is associated with missionary activities within a specified geographic region.
-
E.
associatedWithMissionaryHistory
Indicates a relationship where something is connected or relevant to the activities, legacy, or historical context of missionary work.
- 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_69efd6b156448190bfa15958208395c3 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f664aa283c8190a869d0555eff60c6 |
completed | May 2, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69f663362c008190a22afed262f1e426 |
completed | May 2, 2026, 8:48 p.m. |
| PDg | Predicate description generation | batch_69f6645a615481909b53d94512ecbaf1 |
completed | May 2, 2026, 8:53 p.m. |
Created at: April 27, 2026, 10:03 p.m.