Triple
T9452583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Student Street |
E227929
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Building 32 |
E44621
|
NE 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: Building 32 | Statement: [Student Street, locatedIn, Building 32]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Building 32 Context triple: [Student Street, locatedIn, Building 32]
-
A.
Building 32
chosen
Building 32 is the Ray and Maria Stata Center at MIT, a distinctive Frank Gehry–designed academic complex housing computer science and artificial intelligence research facilities.
-
B.
Building 19
Building 19 is a notable architectural structure within the pre-Columbian Mesoamerican archaeological site of El Tajín in Veracruz, Mexico.
-
C.
Building 46
Building 46 is MIT’s neuroscience and cognitive science hub, housing the Department of Brain and Cognitive Sciences and related research facilities.
-
D.
Building 20
Building 20 is a notable architectural structure within the pre-Columbian Mesoamerican archaeological site of El Tajín in Veracruz, Mexico.
-
E.
Building 12
Building 12, also known as MIT.nano, is MIT’s state-of-the-art nanotechnology research facility housing advanced cleanroom and imaging laboratories for work at the nanoscale.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca8439f8bc8190997f2ef40c9f0bc2 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f68f9b081908bee041d4fc77e57 |
completed | April 1, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1227b4fc881908c03409f78de1a87 |
completed | April 4, 2026, 2:38 p.m. |
Created at: March 30, 2026, 7:52 p.m.