Triple
T10351262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One World Observatory |
E243886
|
entity |
| Predicate | locatedOnFloors |
P74241
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [One World Observatory, locatedOnFloors, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedOnFloors Context triple: [One World Observatory, locatedOnFloors, 100]
-
A.
locatedOnLevel
chosen
Indicates that one entity is situated on a specific floor or level within a multi-level structure or system.
-
B.
locatedOnBuilding
Indicates that one entity is physically situated on the exterior or rooftop surface of a building.
-
C.
locatedIn
Indicates that one entity exists or is situated within the spatial, administrative, or conceptual boundaries of another entity.
-
D.
oftenLocatedAt
Indicates that an entity is frequently or commonly found at, or associated with being in, a particular location.
-
E.
hasOfficeFloors
Indicates that one entity (typically a building or structure) contains floors that are designated or used as office space.
- 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_69d381b22b8c8190aaed476be5f872a9 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9489f9481908fc1c818e81c1cc2 |
completed | April 7, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69d4dfa657f481909cc5cc8fec00ad19 |
completed | April 7, 2026, 10:42 a.m. |
Created at: April 6, 2026, 11:57 a.m.