Triple
T15759213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Holy Monastery of Great Meteoron |
E382047
|
entity |
| Predicate | formerAccess |
P120218
|
FINISHED |
| Object | ladders and nets |
—
|
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: ladders and nets | Statement: [Holy Monastery of Great Meteoron, formerAccess, ladders and nets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formerAccess Context triple: [Holy Monastery of Great Meteoron, formerAccess, ladders and nets]
-
A.
formerUser
Indicates that an entity was previously a user of another entity or system but is no longer one.
-
B.
formerRecord
Indicates that an entity previously held a particular record or status but no longer does so.
-
C.
formerAnchor
Indicates that an entity previously held the role of anchor but no longer does so.
-
D.
formerField
Indicates that an entity previously had a particular field, role, or area of activity, but no longer does.
-
E.
formerMaster
Indicates that one entity previously held the role of master over another entity, but no longer does so.
- 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_69d86d9e6b44819085d1f6a969ecb74c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e050b35ea48190a758ee76a57b5451 |
completed | April 16, 2026, 3 a.m. |
| PD | Predicate disambiguation | batch_69e00531e7ac8190a4190cce4f7fab4c |
completed | April 15, 2026, 9:37 p.m. |
| PDg | Predicate description generation | batch_69e03cc871d0819085c0fc54de7984ff |
completed | April 16, 2026, 1:35 a.m. |
Created at: April 10, 2026, 4:47 a.m.