Triple
T445669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fields Medal |
E7011
|
entity |
| Predicate | hasCitizenshipRestriction |
P13300
|
FINISHED |
| Object | none |
—
|
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: none | Statement: [Fields Medal, hasCitizenshipRestriction, none]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCitizenshipRestriction Context triple: [Fields Medal, hasCitizenshipRestriction, none]
-
A.
countryOfCitizenship
Indicates the country in which a person or entity holds legal citizenship.
-
B.
visaRequirement
Indicates whether one party must obtain a visa in order to enter, stay in, or transit through the territory of another party.
-
C.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
D.
acquireCitizenshipBy
Indicates the process or means by which an entity obtains or is granted citizenship through a specific method, action, or legal basis.
-
E.
laterCitizenship
Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
- F. None of above. chosen
Provenance (4 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_69a2e7e4676c81909ea0dbdecac0687c |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ef479ec08190a659eead6eb0d4d0 |
completed | Feb. 28, 2026, 1:36 p.m. |
| PD | Predicate disambiguation | batch_69a2eddfb5508190a4e06e1b260d8b2b |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.