Triple
T6057364
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butrus |
E134946
|
entity |
| Predicate | usageAmong |
P68012
|
FINISHED |
| Object | Arabic-speaking Christians |
—
|
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: Arabic-speaking Christians | Statement: [Butrus, usageAmong, Arabic-speaking Christians]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageAmong Context triple: [Butrus, usageAmong, Arabic-speaking Christians]
-
A.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
B.
usageToday
Indicates the current or most recent use or application of something on the present day.
-
C.
usagePattern
Indicates how something is typically used or the recurring manner in which it is employed or consumed.
-
D.
usageStatus
Indicates the current state or condition of how something is being used, such as whether it is active, inactive, available, or in use.
-
E.
usesFrequency
Indicates that one entity employs or operates another entity at a specified rate, interval, or number of occurrences over time.
- 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_69c00877b6d4819096b0e163728b73a3 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c0570d00e88190b2d8d596e40378d9 |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:09 p.m.