Triple
T7225110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ghar Hira |
E150358
|
entity |
| Predicate | linkedTextuallyIn |
P19741
|
FINISHED |
| Object | Islamic tradition (Hadith and Sira literature) |
—
|
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 tradition (Hadith and Sira literature) | Statement: [Ghar Hira, linkedTextuallyIn, Islamic tradition (Hadith and Sira literature)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: linkedTextuallyIn Context triple: [Ghar Hira, linkedTextuallyIn, Islamic tradition (Hadith and Sira literature)]
-
A.
linkedNetwork
Indicates that two entities are connected through a shared or associated network relationship.
-
B.
linkedSite
Indicates that one site has an explicit hyperlink or reference connection to another site.
-
C.
linkType
Indicates the specific kind or category of relationship that connects two linked entities.
-
D.
linkedLocation
Indicates that one location is associated or connected to another location in a meaningful way, such as being related, referenced, or contextually tied.
-
E.
linkedDocument
chosen
Indicates that one document is associated with or references another document in a meaningful way.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e9dc835881909ea646c392a980b6 |
completed | March 27, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.