Triple
T33447853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messenger of Allah |
E856555
|
entity |
| Predicate | equivalentPhrase |
P173433
|
FINISHED |
| Object | Messenger of God |
—
|
NE NERFINISHED |
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: Messenger of God | Statement: [Messenger of Allah, equivalentPhrase, Messenger of God]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentPhrase Context triple: [Messenger of Allah, equivalentPhrase, Messenger of God]
-
A.
equivalentEnglishForm
chosen
Indicates that two expressions share the same meaning in English, serving as equivalent linguistic forms.
-
B.
meaningOfPhrase
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
C.
equivalentEpithetLanguage
Indicates that two epithets are expressed in different languages but convey the same meaning or designation.
-
D.
equivalentIn
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
E.
synonym
Indicates that two terms have the same or nearly the same meaning in a given context.
- F. None of above.
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_69f34971b75881908be360bb041f003c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f71fb1ab3881908e2f7c0e6f23db49 |
completed | May 3, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f71cc6397881909aaad37a9daa8a7e |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 1:37 a.m.