Triple
T8487025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MIT.nano |
E200855
|
entity |
| Predicate | hasCleanroomArea |
P61429
|
FINISHED |
| Object | approximately 18,000 square feet |
—
|
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: approximately 18,000 square feet | Statement: [MIT.nano, hasCleanroomArea, approximately 18,000 square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCleanroomArea Context triple: [MIT.nano, hasCleanroomArea, approximately 18,000 square feet]
-
A.
hasIndoorArea
chosen
Indicates that an entity possesses or includes an area or space that is located indoors or within a building.
-
B.
hasRoom
Indicates that an entity possesses, contains, or is associated with a specific room.
-
C.
hasCoreArea
Indicates that an entity possesses a primary or central area that is fundamental to its structure, function, or focus.
-
D.
hasAreaType
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
E.
hasWaitingArea
Indicates that an entity provides or includes a designated space where people can wait before receiving a service or proceeding to another area.
- 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_69ca831d7b148190a6e32c1de43ab13b |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53c4d608190a766c0e919a4b96f |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd107633c8190a36ba50e07876918 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:13 p.m.