Triple
T4608382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rolle |
E100491
|
entity |
| Predicate | hasCastleUse |
P57417
|
FINISHED |
| Object | administrative and cultural venue |
—
|
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: administrative and cultural venue | Statement: [Rolle, hasCastleUse, administrative and cultural venue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCastleUse Context triple: [Rolle, hasCastleUse, administrative and cultural venue]
-
A.
hasCastle
Indicates that one entity possesses, controls, or contains a castle.
-
B.
hasCastleType
Indicates that an entity is associated with, characterized by, or classified as a specific type of castle.
-
C.
hasFamousCastle
Indicates that an entity possesses or is the location of a castle that is widely recognized or renowned.
-
D.
hasTower
Indicates that one entity possesses, contains, or is characterized by the presence of a tower.
-
E.
castleBuilt
Indicates that a castle has been constructed or established, typically by a specific agent or during a particular time period.
- 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_69bd43cce1e08190a07d53af6a9b6c24 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd599debdc81909d11d0e871c666bb |
completed | March 20, 2026, 2:28 p.m. |
| PD | Predicate disambiguation | batch_69bd522e2d5c8190937d0b5574f78f99 |
completed | March 20, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69bd56b5f4648190834eafa666d53caa |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:12 p.m.