Triple
T35725309
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M-6 highway |
E1032595
|
entity |
| Predicate | hasFormerNameOfCityOnRoute |
P40182
|
FINISHED |
| Object | Kirovakan |
—
|
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: Kirovakan | Statement: [M-6 highway, hasFormerNameOfCityOnRoute, Kirovakan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerNameOfCityOnRoute Context triple: [M-6 highway, hasFormerNameOfCityOnRoute, Kirovakan]
-
A.
hasFormerStreetName
Indicates that an entity (such as a street or place) was previously known by a different street name.
-
B.
hasAssociatedCityFormerName
chosen
Indicates that an entity is linked to a city by referencing one of that city's former or historical names.
-
C.
hasPredecessorNameInCity
Indicates that an entity has a predecessor (e.g., an earlier version or prior holder) that had the same name in a specified city.
-
D.
formerNameOfRelatedCity
Indicates that one city previously had a different name that was historically used for another, related city.
-
E.
usesFormerRouteOf
Indicates that one route, service, or pathway currently follows all or part of the alignment or path that was previously used by another route.
- 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_69f76e102b5881909e5d63a30a5cecbe |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fe6e492bf8819080b25221d13445ea |
completed | May 8, 2026, 11:14 p.m. |
| PD | Predicate disambiguation | batch_69fe6dd33a6881908fe9bbbc184cab51 |
completed | May 8, 2026, 11:12 p.m. |
Created at: May 3, 2026, 4:05 p.m.