Triple
T34825313
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taraqi Qila |
E1003904
|
entity |
| Predicate | hasStudyObject |
P16979
|
FINISHED |
| Object | ancient settlement patterns |
—
|
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: ancient settlement patterns | Statement: [Taraqi Qila, hasStudyObject, ancient settlement patterns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStudyObject Context triple: [Taraqi Qila, hasStudyObject, ancient settlement patterns]
-
A.
hasStudyType
Indicates that an entity is associated with or characterized by a particular type or design of study.
-
B.
hasStudyModel
Indicates that an entity is associated with, or defined by, a particular study model used for analysis, simulation, or representation.
-
C.
hasBeenStudiedFor
Indicates that an entity has been the subject of research, examination, or analysis for a specified purpose, topic, or application.
-
D.
hasStudied
Indicates that an entity has engaged in learning or academic work related to another entity (such as a subject, field, or course).
-
E.
notableObjectOfStudy
chosen
Indicates that a subject is a significant or prominent focus of research, analysis, or scholarly attention for 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_69f76db7d1b4819093bd4912d80d845d |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ffc3f0b19c8190b5a749bc3cad21dd |
completed | May 9, 2026, 11:32 p.m. |
| PD | Predicate disambiguation | batch_69ffc1b882808190932b2d43ea5537c9 |
completed | May 9, 2026, 11:22 p.m. |
Created at: May 3, 2026, 4 p.m.