Triple
T13171394
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Astor Place |
E312982
|
entity |
| Predicate | hasUrbanReconstruction |
P72514
|
FINISHED |
| Object | 2010s plaza redesign |
—
|
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: 2010s plaza redesign | Statement: [Astor Place, hasUrbanReconstruction, 2010s plaza redesign]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUrbanReconstruction Context triple: [Astor Place, hasUrbanReconstruction, 2010s plaza redesign]
-
A.
cityRebuiltAfter
Indicates that a city was reconstructed or significantly restored following a prior event of destruction or severe damage.
-
B.
hasMajorReconstruction
chosen
Indicates that an entity has undergone a significant or extensive reconstruction or renovation.
-
C.
hasUrbanContinuity
Indicates that there is a continuous, uninterrupted urbanized area or built-up fabric between the related entities.
-
D.
hasRebuiltHistoricCenter
Indicates that an entity has undertaken and completed the restoration or reconstruction of a historic city or town center.
-
E.
hasUrbanFabric
Indicates that one entity possesses, contains, or is characterized by a particular pattern or structure of built-up urban development.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc2c0c88190be357811aa8e828d |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:13 p.m.