Triple
T34775227
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen Vaidehī |
E1002482
|
entity |
| Predicate | regionOfCulticReception |
P200526
|
FINISHED |
| Object | China |
—
|
NE NERFINISHED |
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: China | Statement: [Queen Vaidehī, regionOfCulticReception, China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionOfCulticReception Context triple: [Queen Vaidehī, regionOfCulticReception, China]
-
A.
typeOfCult
Indicates that one entity is a specific kind or category of cult relative to another entity.
-
B.
culticFormOf
Indicates that one entity is a religious or ritual expression, manifestation, or practice associated with another entity (such as a deity, belief, or tradition).
-
C.
languageUsedInRituals
Indicates that a particular language is employed as the medium of speech, chant, or recitation during specific rituals or ceremonial practices.
-
D.
hasCulticInstallations
Indicates the presence of structures or features specifically designed or used for religious or ritual (cultic) practices.
-
E.
hasCulticPractice
Indicates that an entity engages in, observes, or is associated with a specific religious or ritualistic practice.
- F. None of above. chosen
Provenance (4 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69ff9361943c81909544203cbc998a69 |
completed | May 9, 2026, 8:04 p.m. |
| PD | Predicate disambiguation | batch_69ff913138a08190b59bdc9d8d199eb3 |
completed | May 9, 2026, 7:55 p.m. |
| PDg | Predicate description generation | batch_69ff935f48808190aa6f4834f59d45b8 |
completed | May 9, 2026, 8:04 p.m. |
Created at: May 3, 2026, 3:59 p.m.