Triple
T11710364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Immovable Cultural Monument of National Significance (Georgia) |
E278357
|
entity |
| Predicate | includesExamplesSuchAs |
P100896
|
FINISHED |
| Object | medieval churches in Georgia |
—
|
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: medieval churches in Georgia | Statement: [Immovable Cultural Monument of National Significance (Georgia), includesExamplesSuchAs, medieval churches in Georgia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesExamplesSuchAs Context triple: [Immovable Cultural Monument of National Significance (Georgia), includesExamplesSuchAs, medieval churches in Georgia]
-
A.
includes
Indicates that one entity contains, encompasses, or has another entity as a part, member, or subset.
-
B.
includesSee
Indicates that one entity’s scope, content, or experience contains or encompasses the act of seeing or visual perception involving another entity.
-
C.
includedWith
Indicates that one entity is provided or packaged together as part of another entity.
-
D.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
E.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
- 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_69d6aaff2ce88190b4a1e4b341ad5377 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a49f072c81909c6a964a92e5bc0c |
completed | April 10, 2026, 7:19 a.m. |
| PD | Predicate disambiguation | batch_69d88a7d483081909c2a101087515d74 |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:40 p.m.