Triple
T2408734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Légion d'honneur schools |
E50335
|
entity |
| Predicate | studentResidence |
P16150
|
FINISHED |
| Object | on-campus boarding houses |
—
|
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: on-campus boarding houses | Statement: [Légion d'honneur schools, studentResidence, on-campus boarding houses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: studentResidence Context triple: [Légion d'honneur schools, studentResidence, on-campus boarding houses]
-
A.
studentClassHoused
Indicates that a particular student’s class is accommodated or located within a specific housing or facility.
-
B.
residentialCampus
chosen
Indicates that an educational institution’s campus includes on-site housing where students live as part of the campus community.
-
C.
hasDeanResidence
Indicates that a person holds the position of dean at a particular residence or residential unit.
-
D.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
E.
hostsCampusOf
Indicates that one entity serves as the physical location or site where another entity’s campus is situated or maintained.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:58 p.m.