Triple
T25155920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heiligenkreuz Abbey |
E626311
|
entity |
| Predicate | hasNumberOfMonksApprox |
P99873
|
FINISHED |
| Object | around 90 |
—
|
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: around 90 | Statement: [Heiligenkreuz Abbey, hasNumberOfMonksApprox, around 90]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMonksApprox Context triple: [Heiligenkreuz Abbey, hasNumberOfMonksApprox, around 90]
-
A.
numberOfMonks
chosen
Indicates the quantity or count of monks associated with a given entity or context.
-
B.
numberOfMonksApprox
Indicates an approximate count or estimate of how many monks are involved or present in a given context.
-
C.
hasNoResidentMonks
Indicates that a place or institution does not have any monks residing there.
-
D.
hasApproximateNumberOfMonkeys
Indicates that an entity is associated with an estimated or non-exact count of monkeys.
-
E.
hasNearbyMonastery
Indicates that one entity is located close to or in the vicinity of a monastery.
- 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_69e2ff2834ec8190b0872e2ec3d76023 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f627aedf548190bc9f53c8a2d67b50 |
completed | May 2, 2026, 4:34 p.m. |
| PD | Predicate disambiguation | batch_69f623a4e1048190bbb8dd1253fdcee9 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 18, 2026, 6:30 a.m.