Triple
T15065315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Towns of Falmouth and Mashpee |
E379739
|
entity |
| Predicate | haveLandUse |
P37665
|
FINISHED |
| Object | residential coastal development |
—
|
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: residential coastal development | Statement: [Towns of Falmouth and Mashpee, haveLandUse, residential coastal development]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveLandUse Context triple: [Towns of Falmouth and Mashpee, haveLandUse, residential coastal development]
-
A.
hasLandUseCharacter
Indicates that one entity possesses or is associated with a particular type or pattern of land use.
-
B.
landUseIncludes
chosen
Indicates that a specified land area contains or permits the specified type(s) of land use within its boundaries.
-
C.
hasLandUsePressure
Indicates that an area or entity is subject to demands or stresses from human or other uses of land that may affect its condition or availability.
-
D.
majorLandUse
Indicates the primary way a given area of land is utilized or designated (e.g., residential, commercial, agricultural).
-
E.
otherLandUse
Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedeea750c819082d8823c9ab6c5a2 |
completed | April 15, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:02 a.m.