Triple
T36513923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Adam Fantilli |
E899982
|
entity |
| Predicate | collegeLocation |
P195618
|
FINISHED |
| Object | Ann Arbor, Michigan |
E46153
|
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: Ann Arbor, Michigan | Statement: [Adam Fantilli, collegeLocation, Ann Arbor, Michigan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collegeLocation Context triple: [Adam Fantilli, collegeLocation, Ann Arbor, Michigan]
-
A.
universityLocatedIn
Indicates that a university is situated within or associated with a specific geographic location or administrative region.
-
B.
cityOfInstitution
Indicates the city in which an institution is located or based.
-
C.
studCareerLocation
Indicates the place where a student's academic or professional career activities occur or are based.
-
D.
stateCampus
Indicates that a campus is part of, located within, or administered by a particular state.
-
E.
hasCampusCity
Indicates that an educational institution or campus is located in a particular city.
- F. None of above. chosen
Provenance (5 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_69f76e5dada881909da2d34bc7a9202a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fddac4e2f48190a9301d3422658b29 |
completed | May 8, 2026, 12:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a39f8feac388190a532d8af16634487 |
completed | June 23, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69fdda06969c8190b5d033964ea2a690 |
completed | May 8, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69fddac42c4081908568649058e86458 |
completed | May 8, 2026, 12:44 p.m. |
Created at: May 3, 2026, 4:10 p.m.