Triple
T36749166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Festival Walk |
E907856
|
entity |
| Predicate | retailFloorArea |
P25135
|
FINISHED |
| Object | over 500,000 square feet |
—
|
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: over 500,000 square feet | Statement: [Festival Walk, retailFloorArea, over 500,000 square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: retailFloorArea Context triple: [Festival Walk, retailFloorArea, over 500,000 square feet]
-
A.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
B.
hasRetailArea
chosen
Indicates that an entity possesses or includes a designated space used for retail or commercial sales activities.
-
C.
floorAreaFeature
Indicates a relationship where a specific feature or characteristic is associated with the floor area of an entity or space.
-
D.
lowFloorAreas
Indicates that the subject has floor areas whose sizes are below a specified or typical threshold.
-
E.
hasCasinoFloorArea
Indicates the total floor area occupied by a casino within a given property or facility.
- 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_69f76e76d10881909ec1679bc043108c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69f7c9f5a8848190ba956ff27f44e396 |
completed | May 3, 2026, 10:19 p.m. |
| PD | Predicate disambiguation | batch_69f7c8999a348190abc1895eaa6e036d |
completed | May 3, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:12 p.m.