Triple
T22420114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1900s Living Historical Village |
E554222
|
entity |
| Predicate | hasInterpretiveGoal |
P148100
|
FINISHED |
| Object | historical accuracy |
—
|
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: historical accuracy | Statement: [1900s Living Historical Village, hasInterpretiveGoal, historical accuracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasInterpretiveGoal Context triple: [1900s Living Historical Village, hasInterpretiveGoal, historical accuracy]
-
A.
hasLinguisticGoal
Indicates that an entity is associated with or directed toward achieving a particular linguistic objective or outcome.
-
B.
hasInterpretiveElement
Indicates that something includes or is associated with an element involving interpretation, such as a subjective, analytical, or explanatory component.
-
C.
hasExplicitInterpretation
Indicates that something is associated with a clearly defined and unambiguous meaning or interpretation.
-
D.
containsInterpretationOf
Indicates that one entity includes or embodies an interpretation or understanding of another entity.
-
E.
semanticGoal
Indicates that an entity has a target meaning or intended semantic outcome it aims to achieve or convey.
- 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_69e11e4f2d0c819091aa3558ea2ee630 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1594a58508190b41fd16c8de5f8b4 |
completed | April 29, 2026, 1:05 a.m. |
| PD | Predicate disambiguation | batch_69e8989495bc81909d2699fce5992e28 |
completed | April 22, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69e8aa39e3388190b659d59948ebf3e6 |
completed | April 22, 2026, 11 a.m. |
Created at: April 16, 2026, 8:46 p.m.