Triple
T16940389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jabir ibn Hayyan |
E410934
|
entity |
| Predicate | latinizedName |
P3646
|
FINISHED |
| Object | Geber |
E410934
|
NE 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: Geber | Statement: [Jabir ibn Hayyan, latinizedName, Geber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geber Context triple: [Jabir ibn Hayyan, latinizedName, Geber]
-
A.
Geber
chosen
Geber is the Latinized name of Jabir ibn Hayyan, a pioneering medieval Islamic alchemist often regarded as the father of early chemistry.
-
B.
Godber
Godber is a surname of English origin borne by various notable individuals, including politicians and artists.
-
C.
Givan
Givan is a surname most notably associated with Paul Givan, a Northern Irish politician who has served as First Minister of Northern Ireland.
-
D.
Gerberoy
Gerberoy is a picturesque medieval village in northern France, renowned for its flower-filled streets and artistic heritage.
-
E.
Gsell
Gsell is a surname of Germanic origin borne by various notable individuals, including artists, scholars, and public figures.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cfacdbc48190988ac259712bb9e8 |
completed | April 18, 2026, 6:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfe7e75881908f95b1d859dd67e4 |
completed | May 10, 2026, 6:35 p.m. |
Created at: April 10, 2026, 5:31 a.m.