Triple
T14645603
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bastion of Freedom |
E343839
|
entity |
| Predicate | hasEnglishText |
P97872
|
FINISHED |
| Object | Bastion of Freedom |
—
|
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: Bastion of Freedom | Statement: [Bastion of Freedom, hasEnglishText, Bastion of Freedom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishText Context triple: [Bastion of Freedom, hasEnglishText, Bastion of Freedom]
-
A.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
B.
hasEnglishIncipit
Indicates that an entity has an opening phrase or initial text (incipit) expressed in English.
-
C.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
-
D.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
E.
hasEnglishGloss
chosen
Indicates that one entity serves as the English-language gloss or explanatory translation for the other entity.
- 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_69d822e1a2cc81908e5bb93cf61ce3cc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb4ea6d8481908e6331ca173c646b |
completed | April 14, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69de657359c88190b082e3e9f86fc1d7 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:26 a.m.