Triple
T25814520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of the Prophet |
E650211
|
entity |
| Predicate | hasHonorificMeaning |
P28844
|
FINISHED |
| Object | city of the Prophet Muhammad |
—
|
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: city of the Prophet Muhammad | Statement: [City of the Prophet, hasHonorificMeaning, city of the Prophet Muhammad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHonorificMeaning Context triple: [City of the Prophet, hasHonorificMeaning, city of the Prophet Muhammad]
-
A.
hasHonorificFrom
Indicates that one entity uses or receives a particular honorific title or form of address originating from another entity or source.
-
B.
hasHonorificBasis
Indicates that one entity serves as the basis or justification for assigning an honorific title or respectful form of address to another entity.
-
C.
hasHonorificName
Indicates that an entity is referred to by a formal or respectful title or name used as an honorific.
-
D.
honorificSense
chosen
Indicates that one entity refers to another using an honorific or respectful linguistic form.
-
E.
hasHonorificSystem
Indicates that a language or culture employs a structured system of honorifics to mark social status, respect, or formality in communication.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6691f5e188190b12c7b2eb729a45e |
completed | May 2, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69f66598d6008190a7ca8ff80399fd34 |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 22, 2026, 7:12 a.m.