Triple
T36923884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | castle of St. Aldobrand |
E913281
|
entity |
| Predicate | hasNotableFeatureInText |
P642
|
FINISHED |
| Object | Gothic grandeur |
—
|
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: Gothic grandeur | Statement: [castle of St. Aldobrand, hasNotableFeatureInText, Gothic grandeur]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableFeatureInText Context triple: [castle of St. Aldobrand, hasNotableFeatureInText, Gothic grandeur]
-
A.
hasNotableFeature
chosen
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
B.
hasNotableWord
Indicates that an entity is associated with a word or term that is considered notable, distinctive, or significant in some context.
-
C.
hasNotablePhrase
Indicates that an entity is associated with a specific phrase or expression that is considered notable or characteristic of it.
-
D.
hasTextIn
Indicates that an entity contains or is associated with a specific piece of text within a particular context or location.
-
E.
hasNotableSentence
Indicates that an entity is associated with a particularly important, famous, or otherwise noteworthy sentence.
- 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_69f76e885b848190bad82c87e9525486 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a10036481909c71188b2a0e7f04 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:13 p.m.