Triple
T35035273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ellicott Square Building |
E1010892
|
entity |
| Predicate | wasWorldsLargestOfficeBuilding |
P182028
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Ellicott Square Building, wasWorldsLargestOfficeBuilding, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasWorldsLargestOfficeBuilding Context triple: [Ellicott Square Building, wasWorldsLargestOfficeBuilding, true]
-
A.
One World Trade CenterInstanceOf
Indicates that One World Trade Center belongs to or is classified as a specific type or class of thing (its general category).
-
B.
isMajorOfficeBuildingIn
Indicates that a building is a primary or significant office structure located within a specified geographic or administrative area.
-
C.
wasLargestMunicipalBuildingIn
Indicates that a building held the status of being the largest municipal building within a specified place or jurisdiction.
-
D.
SearsTowerLaterRenamed
Indicates that something originally known as the Sears Tower was later given a different official name.
-
E.
formerTallestBuildingInTheWorld
Indicates that a building once held, but no longer holds, the record for being the tallest building in the world.
- F. None of above. chosen
Provenance (4 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_69f76dcea02c81908542a223f6d5059f |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7865578d48190bf90e470634fd97d |
completed | May 3, 2026, 5:31 p.m. |
| PD | Predicate disambiguation | batch_69f7841812f081909d878955d114088e |
completed | May 3, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69f78575917481909a3defd6a4c366bd |
completed | May 3, 2026, 5:27 p.m. |
Created at: May 3, 2026, 4:01 p.m.