Triple
T15299527
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sentinel Building (Columbus Tower) |
E365746
|
entity |
| Predicate | cityRegisteredLandmark |
P118014
|
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: [Sentinel Building (Columbus Tower), cityRegisteredLandmark, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityRegisteredLandmark Context triple: [Sentinel Building (Columbus Tower), cityRegisteredLandmark, true]
-
A.
primaryCityLandmarkOf
Indicates that a landmark is a principal or defining landmark associated with a specific city.
-
B.
cityLandmarkID
Indicates that a specific landmark is uniquely identified as being located within a particular city.
-
C.
homeCityLandmarkReferencedInNickname
Indicates that a landmark from a person's home city is mentioned or alluded to in their nickname.
-
D.
emblematicBuildingLocation
Indicates that a building serves as a symbolic or representative landmark for a particular location or area.
-
E.
citySymbol
Indicates that one entity serves as the official symbol or emblem representing a particular city.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0368869f8819098cf9e7801e37548 |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
| PDg | Predicate description generation | batch_69decf2e413481909d9180a8d78d2c17 |
completed | April 14, 2026, 11:35 p.m. |
Created at: April 10, 2026, 3:15 a.m.