Triple
T12384673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanzania and Zambia |
E295831
|
entity |
| Predicate | haveCommonReligionGroups |
P37062
|
FINISHED |
| Object | Christianity |
—
|
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: Christianity | Statement: [Tanzania and Zambia, haveCommonReligionGroups, Christianity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveCommonReligionGroups Context triple: [Tanzania and Zambia, haveCommonReligionGroups, Christianity]
-
A.
sharesReligionWith
chosen
Indicates that two entities follow or are associated with the same religion or religious tradition.
-
B.
religiousGroupsPresent
Indicates that one or more religious groups are present or represented in a given context, location, or situation.
-
C.
hasAssociatedReligion
Indicates that an entity is connected with or linked to a particular religion.
-
D.
hasClergyLikeGroup
Indicates that an entity possesses or is associated with a group functioning in a clergy-like or religious-leadership role.
-
E.
ethnicOrReligiousGroup
Indicates that one entity is an ethnic or religious group to which the other entity belongs or with which it is associated.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbc3f608190b0ee3c4f304a94db |
completed | April 10, 2026, 6:21 p.m. |
| PD | Predicate disambiguation | batch_69d93ed256788190b704cad171a4824e |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.