Triple
T8517006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vo Nguyen Giap Road |
E201596
|
entity |
| Predicate | namedForNotabilityOfEponym |
P53948
|
FINISHED |
| Object | military commander |
—
|
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: military commander | Statement: [Vo Nguyen Giap Road, namedForNotabilityOfEponym, military commander]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForNotabilityOfEponym Context triple: [Vo Nguyen Giap Road, namedForNotabilityOfEponym, military commander]
-
A.
namedForNotablePersonFrom
Indicates that one entity is named in honor of a notable person who originates from another specified place or group.
-
B.
hasNamesakeNotability
Indicates that one entity is notable or recognized specifically because it shares the same name as another entity.
-
C.
isNamedForEponymRole
chosen
Indicates that one entity bears a name derived from another entity that serves as its eponym or namesake.
-
D.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
E.
honorificEponym
Indicates that one entity serves as an honorific namesake for another, typically recognizing or commemorating the person or entity in whose honor something is named.
- 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_69ca8321bb44819081b74df0b710276d |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe62550908190af882019d68a904a |
completed | March 31, 2026, 3:20 p.m. |
| PD | Predicate disambiguation | batch_69cbd10f64b4819080859057c19e58f0 |
completed | March 31, 2026, 1:50 p.m. |
Created at: March 30, 2026, 6:15 p.m.