Triple
T14858020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nelson Mandela International Airport |
E349409
|
entity |
| Predicate | namedForEponymRole |
P56375
|
FINISHED |
| Object | anti-apartheid revolutionary |
—
|
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: anti-apartheid revolutionary | Statement: [Nelson Mandela International Airport, namedForEponymRole, anti-apartheid revolutionary]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForEponymRole Context triple: [Nelson Mandela International Airport, namedForEponymRole, anti-apartheid revolutionary]
-
A.
isNamedForEponymRole
Indicates that one entity bears a name derived from another entity that serves as its eponym or namesake.
-
B.
hasEponymConnectionTo
chosen
Indicates that one entity is named after, derived from, or otherwise linguistically or honorifically connected to another entity as its eponym.
-
C.
namedPersonRole
Indicates that a person is identified by name as holding a specific role or position in a given context.
-
D.
eponymKnownFor
Indicates that a person or entity is widely recognized or named as the source or inspiration for something else (such as a concept, place, or object).
-
E.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44598e48190b759a05ed2d9ecaf |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:54 a.m.