Triple
T35332852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 42 Barcelona |
E1020371
|
entity |
| Predicate | tuitionFree |
P135619
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [42 Barcelona, tuitionFree, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tuitionFree Context triple: [42 Barcelona, tuitionFree, true]
-
A.
isTuitionFree
chosen
Indicates that an educational program, institution, or course does not require students to pay tuition fees.
-
B.
isTuitionFreeFor
Indicates that one entity does not require another entity to pay tuition fees for access, enrollment, or participation.
-
C.
tuitionFee
Indicates the amount of money that must be paid for instruction or enrollment in an educational program.
-
D.
tuitionBased
Indicates that something operates, is determined, or is structured based on the amount or presence of tuition fees.
-
E.
tuitionFeeType
Indicates the category or structure of tuition fees that applies to an entity (such as full-time, part-time, in-state, out-of-state, or other fee types).
- 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_69f76deacf4481908e7735a5a7715b0a |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79533b88c8190934ec4cb21770e24 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f79104f5b48190a496cdffde8472da |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.