Triple
T6797327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Campbell Apartment |
E156088
|
entity |
| Predicate | cityLandmarkContext |
P22581
|
FINISHED |
| Object | part of Grand Central Terminal complex |
—
|
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: part of Grand Central Terminal complex | Statement: [Campbell Apartment, cityLandmarkContext, part of Grand Central Terminal complex]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cityLandmarkContext Context triple: [Campbell Apartment, cityLandmarkContext, part of Grand Central Terminal complex]
-
A.
cityLandmarkID
Indicates that a specific landmark is uniquely identified as being located within a particular city.
-
B.
primaryCityLandmarkOf
Indicates that a landmark is a principal or defining landmark associated with a specific city.
-
C.
emblematicBuildingLocation
Indicates that a building serves as a symbolic or representative landmark for a particular location or area.
-
D.
includesLandmark
chosen
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
-
E.
hasTouristAttractionRole
Indicates that an entity serves in the capacity or function of a tourist attraction for another entity (such as a place, organization, or area).
- 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_69c6881844448190a65822d9b39d7f88 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d2ca0c288190a990180fb7cfd08f |
completed | March 27, 2026, 6:56 p.m. |
| PD | Predicate disambiguation | batch_69c6d099bf08819089a9f9894d037e74 |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:15 p.m.