Triple
T8258265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Astoria waterfront redevelopment |
E193123
|
entity |
| Predicate | landUseChangeFrom |
P44099
|
FINISHED |
| Object | industrial |
—
|
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: industrial | Statement: [Astoria waterfront redevelopment, landUseChangeFrom, industrial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: landUseChangeFrom Context triple: [Astoria waterfront redevelopment, landUseChangeFrom, industrial]
-
A.
formerLandUse
chosen
Indicates the type of land use that characterized a location prior to its current or present use.
-
B.
otherLandUse
Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
-
C.
landUseContext
Indicates the contextual setting or circumstances under which a particular piece of land is used or designated for a specific purpose.
-
D.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
E.
primaryLandUse
Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
- 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_69ca82dfad9c8190b8cd18fb89f50f40 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb78fce9308190ac36512e80b06b52 |
completed | March 31, 2026, 7:34 a.m. |
| PD | Predicate disambiguation | batch_69cb36b6d5548190b665a6cce14c69f7 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:49 p.m.