Triple
T32937988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medical Center station |
E842583
|
entity |
| Predicate | servesPrimaryLandUse |
P150180
|
FINISHED |
| Object | medical campus |
—
|
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: medical campus | Statement: [Medical Center station, servesPrimaryLandUse, medical campus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesPrimaryLandUse Context triple: [Medical Center station, servesPrimaryLandUse, medical campus]
-
A.
servesLandUseType
chosen
Indicates that one entity functions to support, accommodate, or provide services for a specified land use type.
-
B.
primaryLandUse
Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
-
C.
secondaryLandUse
Indicates a secondary or additional way in which a piece of land is used, beyond its primary designated use.
-
D.
regionPrimaryUse
Indicates the main functional purpose or dominant activity for which a region is used.
-
E.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
- 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_69f34949727c81909d195c97de3341c8 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69ff48199b1c8190bb05872f8a4f4673 |
completed | May 9, 2026, 2:43 p.m. |
| PD | Predicate disambiguation | batch_69ff4746b1cc8190854f70a124df7d04 |
completed | May 9, 2026, 2:40 p.m. |
Created at: May 1, 2026, 1:20 a.m.