Triple
T28974209
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loba |
E734360
|
entity |
| Predicate | hasEnglishLanguageCounterpart |
P3437
|
FINISHED |
| Object | She Wolf |
—
|
NE NERFINISHED |
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: She Wolf | Statement: [Loba, hasEnglishLanguageCounterpart, She Wolf]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishLanguageCounterpart Context triple: [Loba, hasEnglishLanguageCounterpart, She Wolf]
-
A.
hasCounterpartNameLanguage
Indicates that an entity’s counterpart (e.g., in another context or system) has a name expressed in a specified language.
-
B.
hasEnglishName
chosen
Indicates that an entity is associated with a name expressed in the English language.
-
C.
hasDialectalCounterpart
Indicates that one linguistic form has a corresponding equivalent or variant in another dialect.
-
D.
hasEnglishEdition
Indicates that one entity has a version or edition of itself that is produced or available in the English language.
-
E.
hasLanguageSimilarTo
Indicates that one entity uses or is associated with a language that is similar or closely related to the language used or associated with another 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_69f05b0d1e7c819092baab93d3fe277e |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
Created at: April 28, 2026, 9:07 a.m.