Triple
T20901800
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rafi Marg |
E514686
|
entity |
| Predicate | hasSurroundingBuildingsType |
P52857
|
FINISHED |
| Object | government offices |
—
|
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: government offices | Statement: [Rafi Marg, hasSurroundingBuildingsType, government offices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurroundingBuildingsType Context triple: [Rafi Marg, hasSurroundingBuildingsType, government offices]
-
A.
hasNeighboringBuilding
Indicates that one building is located adjacent to or directly next to another building.
-
B.
hasBuildingStyleInSurroundings
chosen
Indicates that an entity is surrounded by or located in an area characterized by a particular building style.
-
C.
hasSurroundings
Indicates that an entity is located within or encircled by a particular environment, context, or set of surrounding elements.
-
D.
architectOfSurroundingBuildings
Indicates that one entity is the architect responsible for designing the buildings that surround or are adjacent to another specified entity.
-
E.
floorCountOfSurroundingBuildings
Indicates the number of floors in the buildings that are located around or near a given reference building 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_69e0b4f8a1108190bce3d31331290ced |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6e8fc5d488190b62f51c35e768d38 |
completed | April 21, 2026, 3:03 a.m. |
| PD | Predicate disambiguation | batch_69e5c9ac91108190a6700fcdf2f11890 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:47 p.m.