Triple
T6552867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abu Nasr al-Sarraj |
E151169
|
entity |
| Predicate | topicCovered |
P26448
|
FINISHED |
| Object | Sufi states (ahwal) |
—
|
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: Sufi states (ahwal) | Statement: [Abu Nasr al-Sarraj, topicCovered, Sufi states (ahwal)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topicCovered Context triple: [Abu Nasr al-Sarraj, topicCovered, Sufi states (ahwal)]
-
A.
primaryTopicOf
Indicates that a given subject is the main or central topic described by another resource (such as a document, page, or record).
-
B.
featuresTopic
chosen
Indicates that something (such as a work, event, or item) prominently includes, focuses on, or is organized around a particular topic.
-
C.
categoryFocus
Indicates that one entity is the primary subject, theme, or focal point within the broader category defined by the other entity.
-
D.
questionTopic
Indicates that a question is about, concerns, or is primarily focused on a particular topic or subject.
-
E.
typicallyCovers
Indicates that one entity is the kind of thing that usually or normally includes, addresses, or encompasses another entity.
- 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_69c687f3fd60819083bfa583e5bcfa71 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c1b15d3481908ae66e3d7564b352 |
completed | March 27, 2026, 5:43 p.m. |
| PD | Predicate disambiguation | batch_69c6acf6d4148190914b19e9affd8c76 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:51 p.m.