Triple
T9542895
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kotelniki |
E230199
|
entity |
| Predicate | servesCommuterTrafficFrom |
P60625
|
FINISHED |
| Object | Lyubertsy area |
—
|
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: Lyubertsy area | Statement: [Kotelniki, servesCommuterTrafficFrom, Lyubertsy area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: servesCommuterTrafficFrom Context triple: [Kotelniki, servesCommuterTrafficFrom, Lyubertsy area]
-
A.
hasCommuterTraffic
Indicates that there is regular, recurring traffic flow associated with people traveling between their homes and places of work or study.
-
B.
commuterHubFor
chosen
Indicates a location that serves as a primary transit or gathering point for commuters traveling to or from another place.
-
C.
servesGovernmentTraffic
Indicates that an entity provides services or functionality specifically for government-related network or data traffic.
-
D.
commuterServiceTo
Indicates a transportation service that regularly carries commuters to a specified destination.
-
E.
commutesBetween
Indicates a regular pattern of travel back and forth between two locations, typically for work, study, or routine activities.
- 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_69ca847c70b8819088a0a0bad64a50d6 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd98e9be048190bf1f01884ff7c362 |
completed | April 1, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69ccd58bd21881908b860e3ee469af13 |
completed | April 1, 2026, 8:21 a.m. |
Created at: March 30, 2026, 8:01 p.m.