Triple
T15236966
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Orange Krush |
E364149
|
entity |
| Predicate | occupiesSection |
P2574
|
FINISHED |
| Object | student section at State Farm Center |
—
|
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: student section at State Farm Center | Statement: [Orange Krush, occupiesSection, student section at State Farm Center]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: occupiesSection Context triple: [Orange Krush, occupiesSection, student section at State Farm Center]
-
A.
occupies
chosen
Indicates that one entity takes up or resides within a physical or conceptual space belonging to or associated with another entity.
-
B.
occupiesBlock
Indicates that one entity is physically positioned within or taking up space in a specified block or bounded area.
-
C.
occupiedBy
Indicates that a space, position, or role is currently being used, held, or filled by a particular entity.
-
D.
appliesToSectionOf
Indicates that something is relevant or applicable specifically to a particular section or subsection of a larger whole.
-
E.
coversSection
Indicates that one entity includes, addresses, or provides content for a particular section 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_69d85a0dde7481908fc64d1e82d5d20d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e007da7e988190925a9b67b8070bc7 |
completed | April 15, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69deca899d5c8190be4a7c71e1683c69 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:12 a.m.