Triple
T7375236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hindu–Arabic numeral system |
E170106
|
entity |
| Predicate | introducedToRegion |
P76642
|
FINISHED |
| Object | Islamic world |
—
|
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: Islamic world | Statement: [Hindu–Arabic numeral system, introducedToRegion, Islamic world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedToRegion Context triple: [Hindu–Arabic numeral system, introducedToRegion, Islamic world]
-
A.
introducedTo
Indicates that one entity caused or facilitated a first meeting or formal presentation between another entity and a third party.
-
B.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
C.
emergedInRegion
Indicates that something first appeared, originated, or came into existence within a specified geographic region.
-
D.
eligibleRegion
Indicates the geographic area within which something (such as an offer, service, or rule) is valid, applicable, or permitted.
-
E.
mentionsRegion
Indicates that one entity explicitly refers to or cites a specific geographic region in its content or context.
- 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1a780f88190abf11994e307b6ad |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0ebf9c88190af5a4d87d3fd338a |
completed | March 27, 2026, 9:04 p.m. |
Created at: March 27, 2026, 3:07 p.m.