Triple
T25843354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu al-Bashar |
E650996
|
entity |
| Predicate | equivalentTitleOf |
P46701
|
FINISHED |
| Object | Adam |
—
|
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: Adam | Statement: [Abu al-Bashar, equivalentTitleOf, Adam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentTitleOf Context triple: [Abu al-Bashar, equivalentTitleOf, Adam]
-
A.
equivalentOrRelatedTitle
chosen
Indicates that two titles are the same or sufficiently similar in meaning, role, or status to be treated as equivalent or closely related.
-
B.
equivalentTitleInPortuguese
Indicates that one entity has a title that is the equivalent of another entity’s title, specifically in Portuguese.
-
C.
equivalentTitleInJapanese
Indicates that one entity has a corresponding or matching title in Japanese that is equivalent in meaning or usage to the other entity’s title.
-
D.
equivalentTitleInFrench
Indicates that one entity’s title is the equivalent or corresponding title of another entity, specifically expressed in French.
-
E.
equivalentTitleInKorean
Indicates that one title has an equivalent or corresponding title expressed in the Korean language.
- 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_69e7ab38086081908f3a8e7e0c6efd83 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6135293908190809e255bf6334760 |
completed | May 2, 2026, 3:08 p.m. |
| PD | Predicate disambiguation | batch_69f611a72780819082f44e66ca2c6ac9 |
completed | May 2, 2026, 3 p.m. |
Created at: April 22, 2026, 7:50 a.m.