Triple
T35735934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ḥubaysh ibn al-Ḥasan |
E1032886
|
entity |
| Predicate | typeOfTranslator |
P86622
|
FINISHED |
| Object | medical translator |
—
|
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: medical translator | Statement: [Ḥubaysh ibn al-Ḥasan, typeOfTranslator, medical translator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfTranslator Context triple: [Ḥubaysh ibn al-Ḥasan, typeOfTranslator, medical translator]
-
A.
typeOfTranslation
Indicates that one entity is a specific kind or category of translation in relation to another entity.
-
B.
givenByTranslatorTo
Indicates a transfer or provision of something from a translator to another party.
-
C.
transducerType
Indicates the specific kind or category of transducer associated with an entity.
-
D.
sourceTypeTranslated
Indicates that something specifies or records the translated form of a source’s type.
-
E.
associatedWithTranslator
chosen
Indicates a relationship where an entity is linked or connected to a translator, typically as the translator of its content or 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_69f76e10e59081908d81ad9ce22f40b6 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a01cb89ff448190b60ee3d148ce76fc |
completed | May 11, 2026, 12:28 p.m. |
| PD | Predicate disambiguation | batch_6a01ca7604b48190bb8643c17c3a8c85 |
completed | May 11, 2026, 12:24 p.m. |
Created at: May 3, 2026, 4:05 p.m.