Triple
T1259322
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abkhazians |
E12461
|
entity |
| Predicate | traditionalReligionSite |
P2154
|
FINISHED |
| Object | sacred groves |
—
|
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: sacred groves | Statement: [Abkhazians, traditionalReligionSite, sacred groves]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalReligionSite Context triple: [Abkhazians, traditionalReligionSite, sacred groves]
-
A.
religiousTarget
Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
-
B.
traditionalReligionName
Indicates that an entity has a name specifically associated with a traditional or indigenous religion.
-
C.
officialReligion
Indicates that a particular religion is formally recognized and designated as the official or state religion of an entity (such as a country or region).
-
D.
laterReligion
Indicates that one religion or religious affiliation chronologically follows or replaces another for the same entity.
-
E.
religiousElement
chosen
Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
- 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_69a4933352e08190ac617291985e76c0 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bfc3a2848190891e73b351019d5b |
completed | March 1, 2026, 10:37 p.m. |
| PD | Predicate disambiguation | batch_69a4bb6eefbc81908dddd7d2ef368186 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:50 p.m.