Triple
T15081750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Byodo-In Temple |
E360162
|
entity |
| Predicate | hasNoResidentMonks |
P117236
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Byodo-In Temple, hasNoResidentMonks, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNoResidentMonks Context triple: [Byodo-In Temple, hasNoResidentMonks, true]
-
A.
hasNotableMonasticSite
Indicates that an entity possesses or is associated with a monastic site (such as a monastery or convent) that is considered historically, culturally, or religiously significant.
-
B.
hasNearbyMonastery
Indicates that one entity is located close to or in the vicinity of a monastery.
-
C.
hasMonasteryDedicatedTo
Indicates that a place or institution possesses a monastery whose religious dedication is to a specific figure, deity, or sacred concept.
-
D.
containsMonastery
Indicates that one entity includes or encompasses a monastery within its boundaries or composition.
-
E.
numberOfMonks
Indicates the quantity or count of monks associated with a given entity or context.
- 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0027450a48190a84588b6aaf84ebf |
completed | April 15, 2026, 9:26 p.m. |
| PD | Predicate disambiguation | batch_69deb9645b9c8190a5712456dbd78029 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:03 a.m.