Triple
T1508498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Time-Life Building |
E33956
|
entity |
| Predicate | hasPlazaFeature |
P1495
|
FINISHED |
| Object | planters and seating areas |
—
|
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: planters and seating areas | Statement: [Time-Life Building, hasPlazaFeature, planters and seating areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlazaFeature Context triple: [Time-Life Building, hasPlazaFeature, planters and seating areas]
-
A.
hasPlaza
Indicates that an entity includes, contains, or is associated with a plaza as part of its structure or grounds.
-
B.
hasPedestrianPlazaOn
Indicates that a pedestrian plaza is located on, or directly associated with, a specified surface, structure, or area.
-
C.
hasPavilion
Indicates that one entity possesses, includes, or is associated with a pavilion as part of its structure, property, or facilities.
-
D.
hasUrbanFeature
chosen
Indicates that a place or area possesses a specific urban element or infrastructure feature (such as roads, parks, or buildings) as part of its built environment.
-
E.
hasCampusFeature
Indicates that a campus possesses or includes a specific physical or functional feature.
- 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a8e2dd93dc8190a78443900e8d5564 |
completed | March 5, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a88728c150819095cdcdbfcabf4249 |
completed | March 4, 2026, 7:25 p.m. |
Created at: March 4, 2026, 7:24 p.m.