Triple
T19596489
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Meru |
E470361
|
entity |
| Predicate | conceptualLocation |
P92560
|
FINISHED |
| Object | center of the three worlds |
—
|
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: center of the three worlds | Statement: [Mount Meru, conceptualLocation, center of the three worlds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conceptualLocation Context triple: [Mount Meru, conceptualLocation, center of the three worlds]
-
A.
hasConceptualLocation
chosen
Indicates that something is associated with or situated within a particular abstract, conceptual, or non-physical context or domain.
-
B.
addressesConcept
Indicates that one entity deals with, discusses, or responds to the subject matter represented by another entity.
-
C.
subjectLocation
Indicates that one entity is located at, in, or near the place or position specified by another entity.
-
D.
hasSpatialConcept
Indicates a relationship where one entity is associated with, defined by, or characterized through a particular spatial concept or spatial configuration.
-
E.
modelingLocation
Indicates the place or setting where the modeling activity or process occurs.
- 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_69d8e510024481908415c0d616fa6186 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e6407b997881909762c8f919c9cdad |
completed | April 20, 2026, 3:04 p.m. |
| PD | Predicate disambiguation | batch_69e514e166dc8190a0f147e0b4c8bbe7 |
completed | April 19, 2026, 5:46 p.m. |
Created at: April 10, 2026, 1:43 p.m.