Triple
T5013250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Muqaddasi |
E112676
|
entity |
| Predicate | describedAspect |
P40643
|
FINISHED |
| Object | cities |
—
|
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: cities | Statement: [Al-Muqaddasi, describedAspect, cities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describedAspect Context triple: [Al-Muqaddasi, describedAspect, cities]
-
A.
describedIn
Indicates that information about an entity is contained or documented within a specified source, such as a text, document, or media.
-
B.
refersToAspect
chosen
Indicates that one entity specifically references or points to a particular aspect, feature, or component of another entity.
-
C.
describes
Indicates that one entity provides an explanation, representation, or account of another entity or concept.
-
D.
governsAspectOf
Indicates that one entity exercises control, regulation, or determining influence over a particular aspect or component of another entity.
-
E.
depictsAttribute
Indicates that one entity visually represents or illustrates a specific attribute or characteristic of 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_69bd4434acb8819086679dbeccc2fe54 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd730f12a481908a27c15dc73987c6 |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd714cbc448190aa53a8a83d768b64 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:35 p.m.