Triple
T3708208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Sisters (Moscow skyscrapers) |
E80942
|
entity |
| Predicate | inCityCenter |
P25976
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Seven Sisters (Moscow skyscrapers), inCityCenter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inCityCenter Context triple: [Seven Sisters (Moscow skyscrapers), inCityCenter, true]
-
A.
hasCityCentreLocation
chosen
Indicates that something is located in, or directly associated with, the central area of a city.
-
B.
isInCity
Indicates that one entity is located within the geographical boundaries of a specified city.
-
C.
notableCityCenter
Indicates that a location serves as a prominent or significant central area within a city.
-
D.
isDowntownCoreOf
Indicates that a location constitutes the central, most urbanized and commercially dense area of a larger city or metropolitan region.
-
E.
concentratedInCity
Indicates that a large proportion or primary presence of something is located within a particular city.
- 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_69ad8b1793888190a5f70e4b21dc05a1 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc580b08481908391283778d5ce14 |
completed | March 8, 2026, 6:52 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.