Triple
T19926069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Monastery |
E478924
|
entity |
| Predicate | hasTriconchSanctuary |
P137861
|
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: [Red Monastery, hasTriconchSanctuary, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTriconchSanctuary Context triple: [Red Monastery, hasTriconchSanctuary, yes]
-
A.
hasNearbySanctuary
Indicates that one entity has a sanctuary or place of refuge located close to it in space or distance.
-
B.
isInSanctuaryWith
Indicates that two or more entities are located together within the same sanctuary or protected refuge at the same time.
-
C.
hasSanctuary
Indicates that one entity provides or serves as a place of refuge, protection, or safe haven for another entity.
-
D.
isLinkedToSanctuary
Indicates that an entity has a connection or association with a sanctuary, such as being related, directed, or assigned to it.
-
E.
hasOldSanctuary
Indicates that an entity possesses or is associated with an old or former sanctuary.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c992fc8190bd262d528be0e636 |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
| PDg | Predicate description generation | batch_69e543c136b081909cab9394b958390a |
completed | April 19, 2026, 9:06 p.m. |
Created at: April 10, 2026, 1:53 p.m.