Triple
T27172535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Highway |
E682956
|
entity |
| Predicate | hasEnglishExonym |
P3437
|
FINISHED |
| Object | Southern Highway |
—
|
NE NERFINISHED |
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: Southern Highway | Statement: [Southern Highway, hasEnglishExonym, Southern Highway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnglishExonym Context triple: [Southern Highway, hasEnglishExonym, Southern Highway]
-
A.
hasExonym
Indicates that one entity is known by an alternative name or designation in another language or cultural context.
-
B.
hasEnglishName
chosen
Indicates that an entity is associated with a name expressed in the English language.
-
C.
hasEndonym
Indicates that an entity has a name or designation used by native speakers or within its own local language or community.
-
D.
hasOfficialNameInEnglish
Indicates that an entity has an officially recognized name expressed in the English language.
-
E.
exonymStatus
Indicates the status or classification of a name used in one language to refer to a place, people, or entity known by a different name in its own language.
- 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_69eefad086808190ab89816c0c300476 |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 27, 2026, 9:24 a.m.