Triple
T4897290
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New Testament miracles and signs |
E109711
|
entity |
| Predicate | languageUsedAs |
P60517
|
FINISHED |
| Object | “signs and wonders” |
—
|
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: “signs and wonders” | Statement: [New Testament miracles and signs, languageUsedAs, “signs and wonders”]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageUsedAs Context triple: [New Testament miracles and signs, languageUsedAs, “signs and wonders”]
-
A.
languagesUsed
Indicates that one entity uses, employs, or is expressed in one or more languages associated with the other entity.
-
B.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
majorityLanguageOf
Indicates that a given language is the primary or most widely spoken language within a specified group, region, or entity.
-
D.
isWorkingLanguageOf
Indicates that a particular language is officially used as a medium of work, communication, or operation within a specified organization, institution, or context.
-
E.
isWidelySpokenIn
Indicates that a language is spoken by a large portion of the population across many regions or communities within a specified area.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd7060f9988190afdf98eb0a38515d |
completed | March 20, 2026, 4:05 p.m. |
Created at: March 20, 2026, 1:28 p.m.