Triple
T38281167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ibn al-Bayṭār |
E1022082
|
entity |
| Predicate | numberOfSubstancesDescribedInAl-Jami |
P204577
|
FINISHED |
| Object | more than 1400 |
—
|
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: more than 1400 | Statement: [Ibn al-Bayṭār, numberOfSubstancesDescribedInAl-Jami, more than 1400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSubstancesDescribedInAl-Jami Context triple: [Ibn al-Bayṭār, numberOfSubstancesDescribedInAl-Jami, more than 1400]
-
A.
initialNumberOfChemicalsListed
Indicates the original count of distinct chemicals that were recorded or specified at the start of a process or listing.
-
B.
addsRegulatedSubstances
Indicates that one entity introduces or incorporates substances that are subject to regulation into another entity or context.
-
C.
featuresSubstance
Indicates that one entity contains, includes, or is characterized by the presence of a particular substance.
-
D.
alkaloidType
Indicates that one entity is classified as a specific type or category of alkaloid in relation to another entity.
-
E.
containsAlkaloids
Indicates that a substance, organism, or material has alkaloid compounds present within it.
- 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_69f76df0cddc81908d16c1556ff4097f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_6a037cae084081909004d77514c5f286 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a1c850c819088795a7ae59bdeb8 |
completed | May 12, 2026, 7:06 p.m. |
| PDg | Predicate description generation | batch_6a037c84ecbc81908232e5215355f43b |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:30 p.m.