Triple
T38109208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fira Gran Via |
E951608
|
entity |
| Predicate | hasGrossFloorArea |
P24212
|
FINISHED |
| Object | around 240000 square metres |
—
|
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: around 240000 square metres | Statement: [Fira Gran Via, hasGrossFloorArea, around 240000 square metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGrossFloorArea Context triple: [Fira Gran Via, hasGrossFloorArea, around 240000 square metres]
-
A.
hasFloorArea
chosen
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
B.
grossLeasableArea
Indicates the total floor area within a property that is available to be leased to tenants, excluding common or non-leasable spaces.
-
C.
roofArea
Indicates the total surface area covered by the roof of a structure.
-
D.
hasFloorSpaceUse
Indicates how a given area of floor space is allocated or used for specific functions or activities.
-
E.
floorAreaFeature
Indicates a relationship where a specific feature or characteristic is associated with the floor area of an entity or 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_69f76f065ed08190bdfb1b6d817f5b39 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:21 p.m.