Triple
T21489269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wilcahuain |
E530192
|
entity |
| Predicate | mainStructureFloors |
P1514
|
FINISHED |
| Object | three stories |
—
|
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: three stories | Statement: [Wilcahuain, mainStructureFloors, three stories]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainStructureFloors Context triple: [Wilcahuain, mainStructureFloors, three stories]
-
A.
numberOfFloors
Indicates the total count of distinct floor levels that a building or structure has.
-
B.
hasBaseBuildingFloors
Indicates that something (such as a building or structure) has a specified number of floors in its base or main part.
-
C.
hasFloorsAboveGround
Indicates that an entity (typically a building or structure) possesses a specified number of floors that are located above ground level.
-
D.
hasOfficeFloors
Indicates that one entity (typically a building or structure) contains floors that are designated or used as office space.
-
E.
floorCount
chosen
Indicates the number of floors or levels that a building or structure has.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea39e73081908e8d14118f9d1e03 |
completed | April 23, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69e631f6e68081908f5ee4ce7413803e |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:22 p.m.