Triple
T19989971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 5 Infinite Loop |
E494034
|
entity |
| Predicate | buildingNumberOnCampus |
P75186
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [5 Infinite Loop, buildingNumberOnCampus, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: buildingNumberOnCampus Context triple: [5 Infinite Loop, buildingNumberOnCampus, 5]
-
A.
buildingNumber
chosen
Indicates the specific numeric identifier assigned to a building within an address or location.
-
B.
campusStructure
Indicates a structural or organizational relationship between parts of a campus and the campus as a whole (e.g., buildings, facilities, or areas belonging to or forming the campus).
-
C.
campusLandmark
Indicates that something serves as a notable or recognizable landmark located on or associated with a campus.
-
D.
numberOfBuildings
Indicates the total count of buildings associated with a given entity or within a specified context.
-
E.
campusSize
Indicates the physical extent or scale of a campus, typically measured in area or capacity.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65fdecf108190a5b215fd25bc4dda |
completed | April 20, 2026, 5:18 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:30 p.m.